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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_78eea632-7b6"},"title":"Deep Research Agent Tech Lead","description":"<p>We&#39;re seeking a highly technical and strategic Staff/Senior Staff Machine Learning Engineer to act as the Tech Lead for our next-generation deep research agents for the Enterprise.</p>\n<p>This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.</p>\n<p>The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.</p>\n<p><strong>Responsibilities</strong></p>\n<p><strong>Technical Leadership &amp; Vision</strong></p>\n<ul>\n<li>Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.</li>\n</ul>\n<ul>\n<li>Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.</li>\n</ul>\n<ul>\n<li>Core Agent Capabilities Development:</li>\n</ul>\n<p><strong>Advanced Knowledge Retrieval</strong>: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.</p>\n<p><strong>Data Analysis</strong>: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.</p>\n<p><strong>Multimodal Intelligence</strong>: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent&#39;s knowledge base.</p>\n<p><strong>Architecture &amp; Design</strong>: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.</p>\n<p><strong>Technical Excellence</strong>: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.</p>\n<p><strong>Team Leadership &amp; Mentorship</strong></p>\n<ul>\n<li>Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.</li>\n</ul>\n<ul>\n<li>Recruiting &amp; Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.</li>\n</ul>\n<ul>\n<li>Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.</li>\n</ul>\n<p><strong>Basic Qualifications</strong></p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.</li>\n</ul>\n<ul>\n<li>8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.</li>\n</ul>\n<ul>\n<li>2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.</li>\n</ul>\n<ul>\n<li>Deep expertise in Generative AI and Large Language Models (LLMs).</li>\n</ul>\n<ul>\n<li>Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.</li>\n</ul>\n<ul>\n<li>Experience with large-scale distributed systems and real-time data processing.</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Advanced degree (Master&#39;s or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.</li>\n</ul>\n<ul>\n<li>Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.</li>\n</ul>\n<ul>\n<li>Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.</li>\n</ul>\n<ul>\n<li>Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.</li>\n</ul>\n<ul>\n<li>Experience with vector databases and advanced retrieval techniques.</li>\n</ul>\n<ul>\n<li>A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).</li>\n</ul>\n<ul>\n<li>Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.</li>\n</ul>\n<ul>\n<li>Experience driving cross-team technical initiatives that have delivered significant business impact.</li>\n</ul>\n<p><strong>Compensation</strong></p>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. 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Our products provide the high-quality data and full-stack technologies that power the world&#39;s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. 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On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production.</p>\n<p>The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. 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Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.</p>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.</p>\n<p>Salary Range: $167,200-$209,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6365e7d7-511","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale AI","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4636227005","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$167,200-$209,000 USD","x-skills-required":["Python","SQL","Modern data/AI tooling","Statistics","Experimentation","Causal reasoning","Measurement","Data science","Machine learning","Quantitative engineering"],"x-skills-preferred":["Experience in a forward deployed, solutions, consulting, or other client-facing technical role","Experience 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Modern data/AI tooling, Statistics, Experimentation, Causal reasoning, Measurement, Data science, Machine learning, Quantitative engineering, Experience in a forward deployed, solutions, consulting, or other client-facing technical role, Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products, Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow, Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery, Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems, Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling, Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":167200,"maxValue":209000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3ba73370-831"},"title":"Internal Audit IT Manager","description":"<p>Ready to be pushed beyond what you think you’re capable of?</p>\n<p>At Coinbase, our mission is to increase economic freedom in the world.</p>\n<p>We’re seeking a very specific candidate who is passionate about our mission and who believes in the power of crypto and blockchain technology to update the financial system.</p>\n<p>As an Internal Audit IT Manager, you will own end-to-end delivery of complex IT and security audits across our cloud infrastructure, security operations, and crypto-native systems.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Owning end-to-end delivery of IT and security audits, from risk assessment and scoping through planning, fieldwork, testing, reporting, and issue validation,covering cloud infrastructure (AWS, GCP), security operations, identity and access management, data protection, IT asset management, vendor/third-party risk, and key in-scope products and services including blockchain infrastructure, centralized and self-hosted wallets, and cold storage.</li>\n</ul>\n<ul>\n<li>Driving AI-enabled audit execution, designing and implementing data analytics, automation, and Generative AI solutions to modernize how we audit (e.g., continuous monitoring, anomaly detection, automated evidence retrieval, AI-assisted workpaper drafting),while maintaining rigorous human-in-the-loop validation to ensure accuracy and audit-quality conclusions.</li>\n</ul>\n<ul>\n<li>Executing audits aligned with the multi-year IT and security audit roadmap, coordinating coverage with co-sourced partners and cross-functional risk initiatives while ensuring alignment with Coinbase&#39;s enterprise risk profile, technology strategy, and regulatory expectations across regions (US, EMEA, APAC).</li>\n</ul>\n<ul>\n<li>Driving high-quality, risk-based findings and executive-level reporting, distilling key themes, emerging risks, and root causes into clear, concise materials for senior management and the Chief Audit Executive,ensuring findings are appropriately documented and supported by evidence.</li>\n</ul>\n<ul>\n<li>Partnering with technology and security leadership across Engineering, Security, Infrastructure, Product, and Operations to build trusted relationships, challenge control design, and advise on pragmatic, risk-based, scalable remediation while maintaining third-line independence.</li>\n</ul>\n<ul>\n<li>Driving disciplined issue management, ensuring timely, risk-based remediation by management, high-quality root cause analysis, and validation of remediation activities,escalating delays or thematic concerns to senior leadership as needed.</li>\n</ul>\n<ul>\n<li>Evaluating and developing talent, assessing candidates and helping build a high-performing, technically credible audit team.</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>7+ years of experience in IT/security internal audit, technology risk, or first-line security/engineering roles with significant controls exposure.</li>\n</ul>\n<ul>\n<li>Experience working in a fast-paced, cloud-native, or engineering-driven environment where technology and security practices evolve rapidly.</li>\n</ul>\n<ul>\n<li>Hands-on audit experience with cloud platforms (AWS, GCP), including IAM policies, security configurations, logging/monitoring, and CI/CD pipelines.</li>\n</ul>\n<ul>\n<li>AI-forward mindset with demonstrated experience applying Python, SQL, or AI tools to audit or security work, building workflows rather than just prompting.</li>\n</ul>\n<ul>\n<li>Relevant professional certifications (e.g., CISA, CISSP, CIA, CISM) required; CPA or CFE a plus.</li>\n</ul>\n<ul>\n<li>Working knowledge of key frameworks such as NIST CSF, COBIT, SOC 2, and ITIL.</li>\n</ul>\n<ul>\n<li>High EQ and collaborative style.</li>\n</ul>\n<ul>\n<li>Proven ability to translate complex technical findings into clear, executive-ready narratives for both technical and non-technical audiences.</li>\n</ul>\n<ul>\n<li>Ability to manage multiple audits and initiatives across time zones (EMEA, APAC) with minimal oversight.</li>\n</ul>\n<ul>\n<li>Demonstrated leadership and team-development experience, including mentoring, coaching, and managing direct reports.</li>\n</ul>\n<ul>\n<li>Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.</li>\n</ul>\n<p>Nice to have:</p>\n<ul>\n<li>Experience auditing or building blockchain infrastructure, crypto custody, or wallet systems (hot/cold storage).</li>\n</ul>\n<ul>\n<li>Background in a high-growth or rapidly scaling environment with complex, evolving technology stacks.</li>\n</ul>\n<ul>\n<li>Experience with GRC platforms (Workiva, Archer, AuditBoard) or building custom audit automation tooling.</li>\n</ul>\n<ul>\n<li>Familiarity with DORA, MiCA, or crypto-specific regulatory frameworks.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_3ba73370-831","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Coinbase","sameAs":"https://www.coinbase.com/","logo":"https://logos.yubhub.co/coinbase.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/coinbase/jobs/7755116","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$166,345-$195,700 USD","x-skills-required":["IT security","Cloud infrastructure","Security operations","Identity and access management","Data protection","IT asset management","Vendor/third-party risk","Blockchain infrastructure","Centralized and self-hosted wallets","Cold storage","AI-enabled audit execution","Data analytics","Automation","Generative AI","Continuous monitoring","Anomaly detection","Automated evidence retrieval","AI-assisted workpaper drafting","Cloud platforms","IAM policies","Security configurations","Logging/monitoring","CI/CD pipelines","Python","SQL","AI tools","NIST CSF","COBIT","SOC 2","ITIL","CISA","CISSP","CIA","CISM","CPA","CFE"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:58:31.708Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - USA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Finance","industry":"Finance","skills":"IT security, Cloud infrastructure, Security operations, Identity and access management, Data protection, IT asset management, Vendor/third-party risk, Blockchain infrastructure, Centralized and self-hosted wallets, Cold storage, AI-enabled audit execution, Data analytics, Automation, Generative AI, Continuous monitoring, Anomaly detection, Automated evidence retrieval, AI-assisted workpaper drafting, Cloud platforms, IAM policies, Security configurations, Logging/monitoring, CI/CD pipelines, Python, SQL, AI tools, NIST CSF, COBIT, SOC 2, ITIL, CISA, CISSP, CIA, CISM, CPA, CFE","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":166345,"maxValue":195700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3a1ecaac-284"},"title":"Global Leader, Applied AI Architects, Beneficial Deployments","description":"<p>As the Global Leader of Applied AI Architects for Beneficial Deployments, you will lead a team of Applied AI Architects who serve as the primary 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You&#39;ll build and scale a world-class, globally distributed team that turns frontier AI into real impact in education, global health, economic mobility, and life sciences.</p>\n<p>You&#39;ll combine deep technical fluency with the leadership judgment needed to operate across segments, regions, and partner types,from global health foundations to leading research institutions to frontline non-profits. You&#39;ll set the vision for how we scale our expertise from a handful of flagship partnerships to an ecosystem of organisations operating as AI-native, and you&#39;ll be accountable for the team, processes, and cross-functional relationships that make that possible.</p>\n<p>In collaboration with Beneficial Deployment’s Head of Nonprofits, Product, Engineering, Policy, and our broader GTM organisation, you&#39;ll help ensure our partners incorporate Claude into their work responsibly, effectively, and in ways that meaningfully accelerate their missions. You&#39;ll represent Anthropic as a senior technical leader on some of our most visible and consequential partnerships, while maintaining our best-in-class safety standards.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead, grow, and mentor a globally distributed team of Architects supporting mission-driven non-profits across education, global health, economic mobility, and life sciences</li>\n</ul>\n<ul>\n<li>Set the vision, strategy, and operating model for how Applied AI shows up in Beneficial Deployments,from discovery through deployment, and from individual partnerships to ecosystem-wide infrastructure</li>\n</ul>\n<ul>\n<li>Establish hiring plans, team structure, and career development paths as we scale the team globally; set goals and reviews that promote growth, output, and a high bar for technical excellence</li>\n</ul>\n<ul>\n<li>Partner closely with segment leads and senior partner leadership to understand requirements and shape engagements on our highest-impact partnerships</li>\n</ul>\n<ul>\n<li>Drive the design of cohort-based accelerators, Claude Code enablement programmes, and other scalable mechanisms that multiply our impact across many organisations simultaneously</li>\n</ul>\n<ul>\n<li>Identify patterns across partners and segments to inform what we build at the ecosystem level,MCPs, evals, reference implementations, and shared infrastructure</li>\n</ul>\n<ul>\n<li>Collaborate with Product and Engineering to surface partner needs, influence roadmap, and ensure learnings from the field shape how Claude evolves</li>\n</ul>\n<ul>\n<li>Represent Anthropic externally with senior leaders at foundations, non-profits, research institutions, and government-adjacent organisations</li>\n</ul>\n<ul>\n<li>Travel to partner sites globally for workshops, technical deep dives, and relationship building</li>\n</ul>\n<ul>\n<li>Help shape team processes and culture as Beneficial Deployments scales, and contribute to the broader Applied AI leadership community at Anthropic</li>\n</ul>\n<ul>\n<li>Travel is 30-40% due to the global nature of the team (SF, NYC, London and Bengaluru) and events across Beneficial Deployments.</li>\n</ul>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li>10+ years of experience in technical, customer-facing roles (Solutions Architect, Forward Deployed Engineer, Customer Engineer, Sales Engineer, or similar), with meaningful exposure to complex, high-stakes deployments</li>\n</ul>\n<ul>\n<li>7+ years of engineering or technical leadership experience, preferably building and scaling customer-facing or forward-deployed teams globally</li>\n</ul>\n<ul>\n<li>Experience working with or inside mission-driven organisations,education, healthcare, scientific research, global development, or non-profits,and a genuine understanding of the constraints, incentives, and operating realities of these sectors</li>\n</ul>\n<ul>\n<li>Familiarity with common LLM implementation patterns, including prompt engineering, evaluation frameworks, agent frameworks, and retrieval systems; 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Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings.</p>\n<p>Ideally you will have:</p>\n<p>Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial. Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_bfddfcc3-e38","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://www.scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4674911005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,000-$311,000 USD (San Francisco, New York, Seattle) $194,400-$279,000 USD (Hawaii, Washington DC, Texas, Colorado) $162,400-$233,000 USD (St. Louis)","x-skills-required":["Full Stack Development","Cloud-Native Technologies","Data Engineering","AI Application Integration","Problem Solving","Collaboration and Communication","Adaptability and Learning Agility"],"x-skills-preferred":["Docker","Kubernetes","AWS","Azure","GCP","ETL","data modeling","data warehousing","data governance","Large Language Models","prompt engineering","retrieval-augmented generation","agent orchestration"],"datePosted":"2026-04-18T15:57:07.621Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; St. Louis, MO; New York, NY; Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Full Stack Development, Cloud-Native Technologies, Data Engineering, AI Application Integration, Problem Solving, Collaboration and Communication, Adaptability and Learning Agility, Docker, Kubernetes, AWS, Azure, GCP, ETL, data modeling, data warehousing, data governance, Large Language Models, prompt engineering, retrieval-augmented generation, agent orchestration","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":162400,"maxValue":311000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3057d55e-9f7"},"title":"AI Agent Engineer","description":"<p>Imagine having an enterprise-grade AppStore at work, one that ensures you can easily search, request, and gain access to any app you need, precisely when you need it. No more long waiting times with outstanding IT requests. As an AI Agent Engineer at Lumos, you will build and own core AI features, in addition to helping to ensure the health of our engineering systems. You will work across the stack, focusing on areas you are most excited about and that bring value to customers. Beyond your technical work, you will gain leadership opportunities early on as we grow our engineering team. You&#39;ll be involved in scaling the product, the team, and the entire company.</p>\n<p>Your responsibilities will include leading the development of agent pipelines, architecting composable agent SDKs with built-in safety and robust fallback strategies, designing tracing tools and alert dashboards to ensure agent performance and quality, owning the agent lifecycle, collaborating closely with security and operations teams to ensure agent governance and auditability, mentoring and upleveling teammates on best practices in observability and resilience, and solving challenging technical problems across the stack to develop critical customer-facing features.</p>\n<p>We&#39;re looking for engineers who want to shape the next generation of intelligent agents – people who care deeply about building reliable, modular systems and elevating those around them. If you&#39;re energized by architecting robust agent SDKs, creating tools that ensure safety and observability, and mentoring others, you&#39;ll thrive at Lumos.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_3057d55e-9f7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Lumos","sameAs":"https://lumos.com","logo":"https://logos.yubhub.co/lumos.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/lumos/jobs/6629003003","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$175,000 - $300,000","x-skills-required":["AI-driven workflows","Tool-calling systems","Retrieval-augmented generation (RAG) pipelines","Autonomous agentic orchestration","LangChain","LangGraph","API design","System performance","Software architecture","Go","TypeScript","Python","React","Identity and access management systems","SCIM","OAuth2","SAML","IDPs","HRIS tools"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:56:20.231Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Onsite in San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI-driven workflows, Tool-calling systems, Retrieval-augmented generation (RAG) pipelines, Autonomous agentic orchestration, LangChain, LangGraph, API design, System performance, Software architecture, Go, TypeScript, Python, React, Identity and access management systems, SCIM, OAuth2, SAML, IDPs, HRIS tools","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":175000,"maxValue":300000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0b5a4347-f37"},"title":"Sr. Machine Learning Engineer, Monetization Engineering","description":"<p>About this role:</p>\n<p>We&#39;re looking for a Senior Machine Learning Engineer to join our Monetization team. As a key member of the team, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Building cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest</li>\n<li>Partnering closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search)</li>\n<li>Using data-driven methods and leveraging the unique properties of our data to improve candidate retrieval</li>\n<li>Working in a high-impact environment with quick experimentation and product launches</li>\n<li>Keeping up with industry trends in recommendation systems</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>2+ years of industry experience applying machine learning methods</li>\n<li>Degree in computer science, statistics, or related field; or equivalent experience</li>\n<li>End-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies</li>\n<li>Practical knowledge of large-scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems</li>\n</ul>\n<p>Nice to have:</p>\n<ul>\n<li>M.S. or PhD in Machine Learning or related areas</li>\n<li>Publications at top ML conferences</li>\n<li>Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring</li>\n<li>Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration</li>\n<li>Expertise in scalable real-time systems that process stream data</li>\n<li>Passion for applied ML and the Pinterest product</li>\n<li>Background in computational advertising</li>\n</ul>\n<p>Relocation Statement:</p>\n<p>This position is not eligible for relocation assistance.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_0b5a4347-f37","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/","logo":"https://logos.yubhub.co/pinterest.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/pinterest/jobs/6121551","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$189,721-$332,012 USD","x-skills-required":["Machine Learning","Deep Learning","Data Processing Pipelines","Large-Scale Machine Learning Systems","Big Data Technologies","Recommender Systems","Ads Ranking","Retrieval","Targeting","Marketplace Systems"],"x-skills-preferred":["M.S. or PhD in Machine Learning or related areas","Publications at top ML conferences","Experience using Cursor, Copilot, Codex, or similar AI coding assistants","Familiarity with LLM-powered productivity tools","Expertise in scalable real-time systems","Passion for applied ML and the Pinterest product","Background in computational advertising"],"datePosted":"2026-04-18T15:56:06.423Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Deep Learning, Data Processing Pipelines, Large-Scale Machine Learning Systems, Big Data Technologies, Recommender Systems, Ads Ranking, Retrieval, Targeting, Marketplace Systems, M.S. or PhD in Machine Learning or related areas, Publications at top ML conferences, Experience using Cursor, Copilot, Codex, or similar AI coding assistants, Familiarity with LLM-powered productivity tools, Expertise in scalable real-time systems, Passion for applied ML and the Pinterest product, Background in computational advertising","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":189721,"maxValue":332012,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6d46741a-b4c"},"title":"Senior Systems Engineer, OS Automation","description":"<p>CoreWeave is looking for a Senior Systems Engineer who is ready to evolve beyond traditional DevOps. You will start by stabilizing and scaling our Linux OS and Kernel build pipelines. Once the foundation is set, you will lead the transition to AI-native infrastructure, building &#39;smart&#39; workflows that don&#39;t just report errors, but understand and fix them.</p>\n<p>You are a Systems Engineer at heart, but you are ready to apply LLMs, RAG, and predictive modeling to solve infrastructure challenges at scale.</p>\n<p>Our Team&#39;s Stack:</p>\n<ul>\n<li>Languages: Python, Go, bash/sh</li>\n<li>Observability: Prometheus, Victoria Metrics, Grafana</li>\n<li>OS &amp; Kernel: Linux Kernel (custom build), Ubuntu</li>\n<li>Hardware: Intel/AMD/ARM CPUs, Nvidia GPUs, DPUs, Infiniband and Ethernet NICs</li>\n<li>Containerization: Docker, Kubernetes (k8s), KubeVirt, containerd, kubelet</li>\n</ul>\n<p>Responsibilities:</p>\n<ul>\n<li>Pipeline Architecture: Design, maintain, and automate reproducible OS image build pipelines for our massive fleet of GPU-accelerated servers.</li>\n<li>Kernel Distribution: Collaborate with kernel engineers to package, validate, and distribute custom Linux builds across Intel, AMD, and ARM architectures.</li>\n<li>Dependency Management: Build tooling to manage dependencies, versioning, and release workflows, ensuring hermetic builds.</li>\n<li>Telemetry &amp; Metrics: Standardize the collection of build metrics to create a baseline for future AI modeling.</li>\n<li>&#39;Smart&#39; CI/CD &amp; Auto-Remediation: Architect AI agents that ingest and analyze build logs in real-time. Develop systems that auto-triage errors, categorize failure patterns, and generate context-aware fix suggestions for engineering teams.</li>\n<li>Predictive Regression Modeling: Design ML workflows that utilize historical performance data to detect kernel and OS regressions (latency, throughput, stability) in staging environments before they impact production.</li>\n<li>Dynamic Kernel Tuning: Implement closed-loop feedback systems that analyze real-time system metrics and automatically suggest or apply sysctl parameter optimizations for specific customer workloads.</li>\n<li>Next-Gen ChatOps: Engineer LLM-driven interfaces for Slack/internal tools, enabling stakeholders to query build statuses, request log summaries, or provision resources using natural language commands.</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>4+ years of professional experience in Linux Systems Engineering, Release Engineering, or DevOps.</li>\n<li>Deep knowledge of Linux internals (boot process, kernel modules, networking stack).</li>\n<li>Experience with package management (Debian/Ubuntu) and build systems.</li>\n<li>Strong proficiency in Python (essential for the AI integration aspects of this role).</li>\n<li>Demonstrable experience integrating API-based AI models (OpenAI, Anthropic, or local open-source models) into software workflows.</li>\n<li>Understanding of RAG (Retrieval-Augmented Generation) architectures for querying technical documentation or logs.</li>\n<li>Experience building event-driven automation (e.g., using webhooks to trigger analysis agents).</li>\n<li>Familiarity with data structures required for vector search or time-series analysis.</li>\n</ul>\n<p>Nice-to-haves:</p>\n<ul>\n<li>Experience with Kubeflow or MLFlow.</li>\n<li>Background in High-Performance Computing (HPC).</li>\n<li>Experience fine-tuning small language models (SLMs) for code or log analysis tasks.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6d46741a-b4c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"CoreWeave","sameAs":"https://www.coreweave.com","logo":"https://logos.yubhub.co/coreweave.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/coreweave/jobs/4396057006","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$153,000 to $242,000","x-skills-required":["Linux Systems Engineering","Release Engineering","DevOps","Python","API-based AI models","RAG (Retrieval-Augmented Generation)","Event-driven automation","Vector search","Time-series analysis"],"x-skills-preferred":["Kubeflow","MLFlow","High-Performance Computing (HPC)","Small language models (SLMs)"],"datePosted":"2026-04-18T15:55:17.014Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Livingston, NJ / New York City, NY/ Sunnyvale, CA/ Bellevue, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Linux Systems Engineering, Release Engineering, DevOps, Python, API-based AI models, RAG (Retrieval-Augmented Generation), Event-driven automation, Vector search, Time-series analysis, Kubeflow, MLFlow, High-Performance Computing (HPC), Small language models (SLMs)","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":153000,"maxValue":242000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0796e182-42e"},"title":"Sr. Software Engineer, Backend (Search Platform)","description":"<p>About Dialpad</p>\n<p>Dialpad is the AI-native business communications platform. We unify calling, messaging, meetings, and contact center on a single platform - powered by AI that understands every conversation in real time.</p>\n<p>More than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.</p>\n<p>We’re now leading the shift to Agentic AI: intelligent agents that don’t just analyze conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time.</p>\n<p>Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.</p>\n<p>Visit dialpad.com to learn more.</p>\n<p>Being a Dialer</p>\n<p>At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.</p>\n<p>We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.</p>\n<p>We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level.</p>\n<p>We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic.</p>\n<p>Your role</p>\n<p>Dialpad’s Product Engineering organization is responsible for building and maintaining the customer-facing features at scale across all of our cloud-native products and services.</p>\n<p>Every day, millions of users across the world leverage our technology for communicating effectively and efficiently.</p>\n<p>Every engineer on our global engineering team is given the opportunity to take ownership of a large portion of the product where they’re able to see immediate results.</p>\n<p>Combining natural language processing and artificial intelligence with world-class cloud computing, the things you’ll create at Dialpad will shape the future of work,enabling companies to work from anywhere and making business communication more human.</p>\n<p>Dialpad’s Analytics team owns data pipelines, multiple databases, a modular query layer, and rich FE components to deliver intuitive and powerful end-user-facing analytics experiences that allow Dialpad customers to make data-driven business decisions.</p>\n<p>Our teams are highly collaborative and comprise cross-disciplinary professionals, including Product Managers, Designers, QA specialists, as well as Engineers specialising in Data Engineering, Data Science, and Telephony.</p>\n<p>This position reports to the Engineering Manager, who is based in Bengaluru, and the role will be based in our Bengaluru, India Office.</p>\n<p>The position will require a hybrid working arrangement based out of our Bengaluru office.</p>\n<p><strong>What you’ll do</strong></p>\n<ul>\n<li>Contribute to the design, development, and maintenance of information retrieval and distributed systems.</li>\n</ul>\n<ul>\n<li>Build and optimize search engines, including indexers, analyzers, ranking, and re-ranking strategies.</li>\n</ul>\n<ul>\n<li>Work on hybrid search techniques, including dense vector manipulation, rank fusion, and reranking.</li>\n</ul>\n<ul>\n<li>Maintain and enhance highly scalable search platforms with a focus on performance and cost efficiency.</li>\n</ul>\n<ul>\n<li>Ensure high availability, reliability, and fault tolerance in search services.</li>\n</ul>\n<ul>\n<li>Collaborate with cross-functional teams to translate business requirements into technical solutions.</li>\n</ul>\n<ul>\n<li>Develop and optimize real-time distributed systems, microservices, and message-driven architectures.</li>\n</ul>\n<ul>\n<li>Implement and maintain monitoring, alerting, and performance metrics for platform reliability.</li>\n</ul>\n<ul>\n<li>Evaluate and integrate emerging technologies to improve search capabilities.</li>\n</ul>\n<ul>\n<li>Write clean, modular, and well-tested code while following best engineering practices.</li>\n</ul>\n<ul>\n<li>Participate in code reviews to ensure quality, maintainability, and scalability.</li>\n</ul>\n<ul>\n<li>Provide mentorship and technical guidance to junior engineers.</li>\n</ul>\n<p><strong>Skills you’ll bring</strong></p>\n<ul>\n<li>4-7 years of experience in information retrieval or distributed systems engineering.</li>\n</ul>\n<ul>\n<li>Strong understanding of search platforms and experience maintaining search engines at scale.</li>\n</ul>\n<ul>\n<li>Deep knowledge of indexers, analyzers, field mapping, and ranking techniques.</li>\n</ul>\n<ul>\n<li>Experience with NLP/NLU within the context of information retrieval.</li>\n</ul>\n<ul>\n<li>Expertise in dense vector manipulation and optimization.</li>\n</ul>\n<ul>\n<li>Familiarity with hybrid search, rank fusion, and reranking techniques.</li>\n</ul>\n<ul>\n<li>Proficiency in Go and Python 3 (experience with Rust or TypeScript is a plus).</li>\n</ul>\n<ul>\n<li>Strong understanding of distributed systems, microservices, and message-driven architectures.</li>\n</ul>\n<ul>\n<li>Passion for real-time performance optimization and high availability.</li>\n</ul>\n<ul>\n<li>Experience with API design using Swagger, OpenAPI, or equivalent tools.</li>\n</ul>\n<ul>\n<li>Knowledge of gRPC or equivalent RPC protocols.</li>\n</ul>\n<ul>\n<li>Experience with Docker and Kubernetes for containerized deployments.</li>\n</ul>\n<ul>\n<li>Familiarity with cloud platforms (GCP preferred, AWS/Azure optional).</li>\n</ul>\n<ul>\n<li>Hands-on experience with Infrastructure as Code tools like Terraform or Ansible.</li>\n</ul>\n<ul>\n<li>Knowledge of CI/CD frameworks and continuous delivery practices.</li>\n</ul>\n<p>Why Join Dialpad</p>\n<ul>\n<li>Work at the center of the AI transformation in business communications</li>\n</ul>\n<ul>\n<li>Build and ship agentic AI products that are redefining how companies operate</li>\n</ul>\n<ul>\n<li>Join a team where AI amplifies every employee’s impact</li>\n</ul>\n<ul>\n<li>Competitive salary, comprehensive benefits, and real opportunities for growth</li>\n</ul>\n<p>We believe in investing in our people. Dialpad offers competitive benefits and perks, cutting-edge AI tools, and a robust training program that help you reach your full potential.</p>\n<p>We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection.</p>\n<p>Our exceptional culture, repeatedly recognized as a Great Place to Work, ensures that every employee feels valued and empowered to contribute to our collective success.</p>\n<p>Don’t meet every single requirement? If you’re excited about this role and possess the fundamental traits, drive, and strong ambition we seek, but your experience doesn’t meet every qualification, we encourage you to apply.</p>\n<p>Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_0796e182-42e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Dialpad","sameAs":"https://dialpad.com","logo":"https://logos.yubhub.co/dialpad.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/dialpad/jobs/8340906002","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["information retrieval","distributed systems engineering","search platforms","indexers","analyzers","field mapping","ranking techniques","NLP/NLU","dense vector manipulation","optimization","hybrid search","rank fusion","reranking","Go","Python 3","API design","gRPC","Docker","Kubernetes","cloud platforms","Infrastructure as Code","CI/CD frameworks"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:54:55.828Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bengaluru, India"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"information retrieval, distributed systems engineering, search platforms, indexers, analyzers, field mapping, ranking techniques, NLP/NLU, dense vector manipulation, optimization, hybrid search, rank fusion, reranking, Go, Python 3, API design, gRPC, Docker, Kubernetes, cloud platforms, Infrastructure as Code, CI/CD frameworks"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3a17bc01-d7d"},"title":"Staff Software Engineer","description":"<p>DBT Labs is seeking a Staff Software Engineer to join our Engineering team. 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As an AI Engineer on the Paige team, you&#39;ll shape the technical vision and execution of our autonomous AI compensation analyst. 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We&#39;re a hybrid culture that brings teams together in person on Monday, Tuesday, Thursday, and Friday, with a weekly Team Sync on Fridays.</p>\n<p><strong>How to Apply</strong></p>\n<p>If you&#39;re ready to help shape the future of compensation alongside a talented team, we&#39;d love to meet you. Please submit your application, including your resume and a cover letter, to [insert contact information].</p>\n<p><strong>Note</strong></p>\n<p>This job description is subject to change based on business needs and requirements. Pave is an equal opportunity employer and welcomes applications from diverse candidates.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_90e31ab7-e71","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Pave","sameAs":"https://pave.com","logo":"https://logos.yubhub.co/pave.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/paveakatroveinformationtechnologies/jobs/4660955005","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$166,600 - $225,400 (P3) or $195,500 - $264,500 (P4)","x-skills-required":["LLMs","Agentic architectures","Retrieval systems","Pragmatic engineering judgment","Communication skills"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:53:27.986Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA & New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, Agentic architectures, Retrieval systems, Pragmatic engineering judgment, Communication skills","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":166600,"maxValue":264500,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fdfef6df-396"},"title":"AI Solutions Engineer","description":"<p>About Pinterest:</p>\n<p>Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime.</p>\n<p>At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.</p>\n<p>Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work.</p>\n<p>Creating a career you love? It’s Possible.</p>\n<p>At Pinterest, AI isn&#39;t just a feature, it&#39;s a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that.</p>\n<p>To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.</p>\n<p>Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think.</p>\n<p>You can read more about our AI interview philosophy and how we use AI in our recruiting process here.</p>\n<p>We&#39;re building a new capability at Pinterest: embedding AI-native engineering directly inside our business functions. 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You understand data access controls, the risks of giving AI broad access to sensitive information, PII minimization, audit logging, and what responsible data handling looks like in an enterprise environment.</li>\n<li>Business function acumen. You can engage credibly with stakeholders in Marketing, Finance, Sales, HR, Legal, or Operations , understanding their workflows, KPIs, and constraints well enough to scope solutions that fit their real needs.</li>\n<li>Clear, collaborative communication. You can explain architecture trade-offs to a Finance Manager and debug a prompt failure with an engineer in the same afternoon.</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience working embedded with or alongside corporate / G&amp;A functions (Finance, Legal, HR, Marketing, Sales Operations, or similar).</li>\n<li>Practical experience with agentic frameworks such as LangGraph, Claude Agent SDK, or comparable tooling.</li>\n<li>Familiarity with MCP server design , including building, deploying, and securing MCP-compliant tool servers.</li>\n<li>Experience designing and evaluating AI outputs at scale: eval sets, sampling pipelines, human-in-the-loop review queues, or A/B testing of AI-powered features.</li>\n<li>Exposure to responsible AI frameworks: data minimization, differential privacy concepts, model output auditing, or working in PII-sensitive / regulated domains.</li>\n<li>Experience with RAG (Retrieval-Augmented Generation) pipelines, vector databases, or enterprise search integrations.</li>\n<li>Familiarity with CI/CD for AI: prompt versioning, model version pinning, regression testing for LLM-powered features.</li>\n</ul>\n<p>Relocation Statement:</p>\n<p>This position is not eligible for relocation assistance.</p>\n<p>Visit our PinFlex page to learn more about our working model.</p>\n<p>In-Office Requirement Statement:</p>\n<p>This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country.</p>\n<p>#LI-REMOTE #LI-KBF</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fdfef6df-396","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/","logo":"https://logos.yubhub.co/pinterest.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/pinterest/jobs/7714127","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Software engineering foundation","Hands-on AI and automation delivery","Agentic AI literacy","System design and architecture thinking","Data and security judgment","Business function acumen","Clear, collaborative communication"],"x-skills-preferred":["Experience working embedded with or alongside corporate / G&A functions","Practical experience with agentic frameworks","Familiarity with MCP server design","Experience designing and evaluating AI outputs at scale","Exposure to responsible AI frameworks","Experience with RAG (Retrieval-Augmented Generation) pipelines","Familiarity with CI/CD for AI"],"datePosted":"2026-04-18T15:52:21.923Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, Seattle, WA, US; Remote, US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Software engineering foundation, Hands-on AI and automation delivery, Agentic AI literacy, System design and architecture thinking, Data and security judgment, Business function acumen, Clear, collaborative communication, Experience working embedded with or alongside corporate / G&A functions, Practical experience with agentic frameworks, Familiarity with MCP server design, Experience designing and evaluating AI outputs at scale, Exposure to responsible AI frameworks, Experience with RAG (Retrieval-Augmented Generation) pipelines, Familiarity with CI/CD for AI"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b2efa219-a4e"},"title":"Senior Software Engineer - Search","description":"<p>We are seeking a Senior Software Engineer to join our Applied AI team at the forefront of advancing AI/ML-powered products. The successful candidate will drive enhancements to our Search Quality, focusing on enhancing search ranking, improving query understanding, building robust evals, and growing the coverage of assets to enable seamless search at scale.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Developing and deploying ML-based search and discovery relevance models and systems integrated with Databricks&#39; products and services.</li>\n<li>Designing and implementing automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration.</li>\n<li>Collaborating with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience.</li>\n<li>Contributing to building a robust framework for evaluating search ranking improvements - both offline and online.</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>A Bachelor&#39;s degree in Computer Science or a related field, with a Master&#39;s or PhD preferred.</li>\n<li>5+ years of experience developing search relevance systems at scale in production or in high-impact research environments.</li>\n<li>Experience applying LLM to search relevance.</li>\n<li>Strong understanding of computer science fundamentals.</li>\n<li>Contributions to well-used open-source projects.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b2efa219-a4e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://databricks.com","logo":"https://logos.yubhub.co/databricks.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/databricks/jobs/7841782002","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["ML","NLP","search relevance","data preprocessing","query understanding","ranking and retrieval","model evaluation","computer science fundamentals"],"x-skills-preferred":["LLM","automated ML pipelines","open-source projects"],"datePosted":"2026-04-18T15:50:57.913Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bengaluru, India"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML, NLP, search relevance, data preprocessing, query understanding, ranking and retrieval, model evaluation, computer science fundamentals, LLM, automated ML pipelines, open-source projects"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_70312463-fa2"},"title":"Senior Software Engineer - AI Platform (NYC)","description":"<p>We are seeking a Senior Software Engineer to join our NYC Engineering office. As one of the first engineers in the office, you will have the opportunity to be part of a small, nimble team that&#39;s innovating to build new products from the ground up. Our goal is to leverage the power of Databricks in data &amp; AI to deliver vertical AI applications for both technical and business users.</p>\n<p>The impact you&#39;ll have:</p>\n<ul>\n<li>Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency</li>\n<li>Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user &amp; business growth</li>\n<li>Lead by example with hands-on full-stack software development to create dynamic, user-centric experiences</li>\n<li>Enable mechanisms that can drive product-led growth, through seamless onboarding and sharing capabilities</li>\n<li>Direct the future of intuitive agentic applications at Databricks, in collaboration with cross-functional teams of innovative software engineers, product managers, and designers</li>\n<li>Drive the strategy for building end-to-end AI feature development by designing, building, and maintaining systems that are scalable, reliable, and performant.</li>\n</ul>\n<p>What we look for:</p>\n<ul>\n<li>5+ years of experience with HTML, CSS, and JavaScript</li>\n<li>Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback.</li>\n<li>You care that AI features feel intuitive, trustworthy, and helpful, not just bolted on to an existing app</li>\n<li>High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption.</li>\n<li>Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives.</li>\n<li>Experience with modern JavaScript frameworks (e.g., React, Angular, or VueJs/Ember)</li>\n<li>5+ years of experience with server-side web technologies (eg: Node.js, Java, Python, Scala, C#, C++,Go)</li>\n<li>Proven experience building and shipping end-to-end generative AI products</li>\n<li>Deep familiarity with LLMs and generative AI, including hands-on experience with techniques like retrieval-augmented generation (RAG), prompt design, evaluation, and monitoring AI quality and safety in production.</li>\n</ul>\n<p>Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. 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You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration.</p>\n<p>A Typical Day:</p>\n<ul>\n<li>Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability</li>\n<li>Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions</li>\n<li>Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact</li>\n<li>Collaborate with other engineers and cross-functional partners across Messaging, Trust &amp; Safety, Localization, and Platform organizations to align on long-term technical solutions</li>\n<li>Mentor, guide, advocate, and support the career growth of individual contributors</li>\n<li>Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation</li>\n</ul>\n<p>Your Expertise:</p>\n<ul>\n<li>9+ years of relevant engineering hands-on work experience</li>\n<li>Bachelors, Masters, or PhD in CS or related field</li>\n<li>Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring</li>\n<li>Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications</li>\n<li>Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding</li>\n<li>Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering</li>\n<li>Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution</li>\n<li>Experience operating distributed, real-time systems at scale with high reliability requirements</li>\n<li>Experience with real-time messaging systems or event-driven architectures</li>\n<li>Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)</li>\n<li>Prior work on trust &amp; safety, content moderation, or internationalization in a messaging context</li>\n<li>Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning</li>\n</ul>\n<p>How We&#39;ll Take Care of You:</p>\n<p>Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.</p>\n<p>Pay Range: $204,000-$255,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_e3b1c38b-ef1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Airbnb","sameAs":"https://www.airbnb.com/","logo":"https://logos.yubhub.co/airbnb.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/airbnb/jobs/7655958","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$204,000-$255,000 USD","x-skills-required":["ML-powered product features","model serving","feature pipelines","online/offline evaluation","monitoring","architectural patterns","NLP/NLU techniques","large language models","messaging","conversational AI","content understanding","distributed, real-time systems","real-time messaging systems","event-driven architectures","ML infrastructure","feature stores","model registries","online inference platforms","trust & safety","content moderation","internationalization","LLM-based product features","prompt engineering","retrieval-augmented generation","fine-tuning"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:49:16.839Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - USA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML-powered product features, model serving, feature pipelines, online/offline evaluation, monitoring, architectural patterns, NLP/NLU techniques, large language models, messaging, conversational AI, content understanding, distributed, real-time systems, real-time messaging systems, event-driven architectures, ML infrastructure, feature stores, model registries, online inference platforms, trust & safety, content moderation, internationalization, LLM-based product features, prompt engineering, retrieval-augmented generation, fine-tuning","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":204000,"maxValue":255000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d7e1a365-9dd"},"title":"Principal Software Engineer II - Search Management - Elasticsearch","description":"<p>We&#39;re looking for a Principal Software Engineer to join the Elasticsearch - Search Management team. This globally-distributed team of experienced engineers focuses on delivering a robust and feature-rich search experience, including contributing to improving the search experience in Lucene.</p>\n<p>As a Principal Software Engineer, you will be a full-time Elasticsearch contributor, building data-intensive new features and fixing intriguing bugs, all while making the code easier to understand. You&#39;ll work with a globally distributed team of experienced engineers focused on the search capabilities of Elasticsearch.</p>\n<p>You&#39;ll be an expert in several areas of Elasticsearch and everyone will turn to you when they have a question about them. You&#39;ll improve those areas based on your questions and your instincts.</p>\n<p>You&#39;ll help us create the future of search within Elasticsearch - building a scalable search tier for our Serverless platform and writing search functionality in ES|QL, our new piped query language as two examples.</p>\n<p>You&#39;ll work with community members from all over the world on issues and pull requests, sometimes triaging them and handing them off to other experts and sometimes handling them yourself.</p>\n<p>You&#39;ll write idiomatic modern Java -- Elasticsearch is 99.8% Java!</p>\n<p>We&#39;re looking for someone with strong skills in core Java and a conversant in the standard library of data structures and concurrency constructs, as well as newer features like lambdas. You should be comfortable developing collaboratively, giving and receiving feedback on code and approaches and APIs.</p>\n<p>You&#39;ve used several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra and have some idea how they work and why they work that way.</p>\n<p>You have excellent verbal and written communication skills. Like we said, collaborating on the internet is hard. We try to be respectful, empathetic, and trusting in all of our interactions. And we&#39;d expect that from you too.</p>\n<p>Bonus points if you&#39;ve built things with Elasticsearch before, worked in the search and information retrieval space, or have experience writing code for software-as-a-service or platforms-as-a-service.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d7e1a365-9dd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Elastic","sameAs":"https://www.elastic.co/","logo":"https://logos.yubhub.co/elastic.co.png"},"x-apply-url":"https://job-boards.greenhouse.io/elastic/jobs/7699084","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$154,000-$243,600 CAD","x-skills-required":["core Java","standard library of data structures and concurrency constructs","newer features like lambdas","data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra","idiomatic modern Java"],"x-skills-preferred":["search and information retrieval space","software-as-a-service or platforms-as-a-service","collaborative development","code review","API design"],"datePosted":"2026-04-18T15:49:07.452Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Canada"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"core Java, standard library of data structures and concurrency constructs, newer features like lambdas, data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra, idiomatic modern Java, search and information retrieval space, software-as-a-service or platforms-as-a-service, collaborative development, code review, API design","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":154000,"maxValue":243600,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_16b7d9c0-0bf"},"title":"Senior Salesforce Engineer","description":"<p>We are seeking an independent Senior Salesforce Engineer who effectively balances technical excellence with a disciplined approach to the software development lifecycle.</p>\n<p>In this role, you will serve as a guardian of our codebase through implementation, rigorous peer reviews, automated testing, and comprehensive deployment support, ensuring the architectural integrity of our environments.</p>\n<p>Key Responsibilities:</p>\n<p>Technical Implementation: Lead the translation of user stories into robust, scalable technical designs. Responsible for the end-to-end execution of features, ensuring alignment with organisational standards.</p>\n<p>Solution Design and Architecture: Architect and design secure, scalable solutions by translating complex business requirements into technical specifications and solution designs that leverage the Salesforce platform, particularly within the Sales and CPQ domains.</p>\n<p>Quality Assurance and Testing: Ensure 100% unit test coverage for all new logic. Build and maintain an automated test regression suite to minimise manual overhead and proactively identify regressions.</p>\n<p>Code and Peer Mentorship: Conduct thorough Pull Request (PR) reviews, providing constructive feedback to junior and mid-level developers to maintain code quality and consistency.</p>\n<p>Deployment and Release Support: Manage the deployment cycle, including documenting all changes, securing necessary Jira approvals, resolving environment-specific test issues, and performing final validation in Production.</p>\n<p>Global Collaboration &amp; Ownership: Demonstrated strong ownership and the ability to communicate effectively and collaborate seamlessly with cross-functional, global teams and stakeholders.</p>\n<p>Required Qualifications:</p>\n<p>Salesforce Development Expertise (5+ years): Proven proficiency in Salesforce development, including Apex, Process/Flow Automations, and Lightning Web Components (LWC).</p>\n<p>Software Development Acumen (3+ years): Strong background in general software engineering principles, with significant experience in Java, Python, or JavaScript.</p>\n<p>Domain Specific Knowledge: In-depth knowledge and practical experience within Sales Cloud and Configure, Price, Quote (CPQ) domains are essential.</p>\n<p>Advanced AI Agent Frameworks &amp; Data Processing: Expertise in modern AI agent or agentforce frameworks, orchestration techniques, Retrieval-Augmented Generation (RAG) pipelines, and advanced vector search methodologies.</p>\n<p>CI/CD Pipeline Proficiency: Hands-on experience with continuous integration and continuous deployment (CI/CD) pipelines, specifically utilising Jenkins and Salesforce DX (SFDX) for efficient development and release.</p>\n<p>Secure Salesforce Solution Development: Deep understanding and practical application of Salesforce security features, adherence to data privacy regulations, and implementation of best practices for secure solution development.</p>\n<p>Communication, &amp; Problem-Solving: Possesses excellent communication and robust problem-solving abilities. Capable of independently driving technical direction, mentoring team members, fostering collaboration, and effectively managing all project aspects.</p>\n<p>Preferred Qualifications (Extra Credit):</p>\n<p>Salesforce certifications, such as Platform Developer I/II, CPQ Administrator, Application Architect, or Technical Architect.</p>\n<p>Experience designing or implementing advanced Salesforce DevOps practices.</p>\n<p>Previous work in a high-growth, SaaS, fast-paced technology company.</p>\n<p>The annual base salary range for this position for candidates located in Poland is between 225 000 zł-330 000 zł PLN.</p>\n<p>Okta offers equity (where applicable), bonus, and comprehensive healthcare coverage and financial benefits including paid time off and parental leave in accordance with our applicable plans and policies.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_16b7d9c0-0bf","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Okta","sameAs":"https://www.okta.com","logo":"https://logos.yubhub.co/okta.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/okta/jobs/7626022","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"225 000 zł-330 000 zł PLN","x-skills-required":["Salesforce development","Apex","Process/Flow Automations","Lightning Web Components (LWC)","Java","Python","JavaScript","Sales Cloud","Configure, Price, Quote (CPQ)","AI agent or agentforce frameworks","orchestration techniques","Retrieval-Augmented Generation (RAG) pipelines","advanced vector search methodologies","CI/CD pipelines","Jenkins","Salesforce DX (SFDX)"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:45:42.155Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Warsaw, Poland"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Salesforce development, Apex, Process/Flow Automations, Lightning Web Components (LWC), Java, Python, JavaScript, Sales Cloud, Configure, Price, Quote (CPQ), AI agent or agentforce frameworks, orchestration techniques, Retrieval-Augmented Generation (RAG) pipelines, advanced vector search methodologies, CI/CD pipelines, Jenkins, Salesforce DX (SFDX)"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c29d72ae-6be"},"title":"Staff Software Engineer- Search Quality","description":"<p>We are seeking a Staff Software Engineer- Search Quality to join our team. As a key member of our engineering team, you will be responsible for building the retrieval backbone for our AI agents and improving the traditional search experience for our users.</p>\n<p>The ideal candidate will have a strong background in information retrieval, machine learning, and software engineering. You will be working on a highly complex and challenging problem, balancing traditional keyword-based search with semantic vector search, and fine-tuning ranking models to satisfy both human readability and LLM-ready context.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Own the quality of results for our AI agents and human users</li>\n<li>Optimize the retrieval layer for LLMs to reason over data they weren’t trained on</li>\n<li>Improve the traditional search experience for employees to find assets and answers through intuitive, high-recall interfaces</li>\n<li>Build the guardrails and relevance scoring to ensure our AI stays grounded in reality</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Strong background in information retrieval, machine learning, and software engineering</li>\n<li>Experience with Lucene/Elasticsearch, embeddings, and ranking algorithms</li>\n<li>Understanding of relevance metrics (nDCG, MRR, Precision@K)</li>\n<li>Ability to work on a highly complex and challenging problem</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive benefits and perks that meet the needs of all employees</li>\n<li>Opportunity to work on a highly complex and challenging problem</li>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<p>About Databricks:</p>\n<p>Databricks is a data and AI company that provides a platform for unifying and democratizing data, analytics, and AI. Over 10,000 organizations worldwide, including many Fortune 500 companies, rely on Databricks.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c29d72ae-6be","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://databricks.com","logo":"https://logos.yubhub.co/databricks.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/databricks/jobs/8439348002","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Lucene/Elasticsearch","embeddings","ranking algorithms","information retrieval","machine learning"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:45:10.522Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bengaluru, India"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Lucene/Elasticsearch, embeddings, ranking algorithms, information retrieval, machine learning"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_061e824c-343"},"title":"Software Engineer: Distributed Systems (Infrastructure)","description":"<p>About Us</p>\n<p>At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world&#39;s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.</p>\n<p>We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.</p>\n<p>Responsibilities</p>\n<p>As a Software Engineer: Distributed Systems, you will be part of a Resiliency Organization responsible for the core services that power Cloudflare&#39;s global operations. We are looking for engineers to join the Infrastructure Intelligence team and shape the transition toward model-driven network orchestration.</p>\n<p>The team is building a cutting-edge &#39;Maintenance Coordination System&#39;, powered by an infrastructure dependency graph of one of the world&#39;s largest physical networks. This is a foundational step towards designing intelligent, autonomous systems that will transform the orchestration of Cloudflare&#39;s network.</p>\n<p>It forms the basis of many future projects to build the core data structures and services required to ensure our network optimization, network forecasting, and capacity planning are the state of the art. By creating the robust primitives for global coordination today, you will be enabling the next generation of data-driven infrastructure at Cloudflare.</p>\n<p>This is a unique opportunity to work on complex, globally distributed systems which underpin all Cloudflare products.</p>\n<p>Technologies we use:</p>\n<ul>\n<li>Cloudflare Workers, Workers KV, R2, and Durable Objects</li>\n</ul>\n<ul>\n<li>Kubernetes</li>\n</ul>\n<ul>\n<li>Go, Typescript, Python</li>\n</ul>\n<ul>\n<li>For service monitoring we use Prometheus, Grafana and Sentry</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>A degree in Computer Science, Engineering, Mathematics, Statistics or related field; OR have relevant background/experience to the field.</li>\n</ul>\n<ul>\n<li>Programming experience in Go, or similar languages</li>\n</ul>\n<ul>\n<li>Experience in designing and implementing secure and highly-available distributed systems</li>\n</ul>\n<ul>\n<li>Experience (and love) for debugging to ensure the system works in all cases</li>\n</ul>\n<ul>\n<li>Experience with a continuous integration workflow and using source control (we use git)</li>\n</ul>\n<ul>\n<li>Experience with continuous delivery and deployment of a k8s hosted application</li>\n</ul>\n<ul>\n<li>Understanding of security issues and responsibilities</li>\n</ul>\n<ul>\n<li>Experience with monitoring, alerting and debugging high volume production systems</li>\n</ul>\n<ul>\n<li>Fluent in analyses of data sets such as logs</li>\n</ul>\n<ul>\n<li>Strong English language oral and written communications skills</li>\n</ul>\n<ul>\n<li>Designing and building APIs</li>\n</ul>\n<ul>\n<li>Experience with the Cloudflare development stack is a plus</li>\n</ul>\n<p>Examples of desirable skills, knowledge and experience</p>\n<ul>\n<li>At least 4 years of hands-on software development experience on meaningfully complex systems.</li>\n</ul>\n<ul>\n<li>Experience with graph theory and building services for graph generation, storage and retrieval.</li>\n</ul>\n<ul>\n<li>An understanding of the systems architecture required to scale machine learning model-driven decision engines in a production environment</li>\n</ul>\n<ul>\n<li>Experience building both backend systems and frontend widgets.</li>\n</ul>\n<ul>\n<li>Ability to contribute to planning, development, and execution to meet commitments and deliver with predictability.</li>\n</ul>\n<ul>\n<li>Experience implementing tools, processes, internal instrumentation, and methodologies.</li>\n</ul>\n<ul>\n<li>Comfortable working on projects with tight deadlines and short release cycles.</li>\n</ul>\n<ul>\n<li>Strong verbal and written English language skills.</li>\n</ul>\n<ul>\n<li>Experience with DCIM, CMDB, IPAM, and other Data Center and Asset Lifecycle Management tools is a plus.</li>\n</ul>\n<ul>\n<li>Experience with data ingestion and analysis - pulling metrics from hundreds of edge data centers.</li>\n</ul>\n<p>Compensation</p>\n<p>For Washington D.C. based hires: Estimated annual salary of $140,000 - 172,000.</p>\n<p>Equity</p>\n<p>This role is eligible to participate in Cloudflare&#39;s equity plan.</p>\n<p>Benefits</p>\n<p>Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!</p>\n<p>The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.</p>\n<p>Health &amp; Welfare Benefits</p>\n<ul>\n<li>Medical/Rx Insurance</li>\n</ul>\n<ul>\n<li>Dental Insurance</li>\n</ul>\n<ul>\n<li>Vision Insurance</li>\n</ul>\n<ul>\n<li>Flexible Spending Accounts</li>\n</ul>\n<ul>\n<li>Commuter Spending Accounts</li>\n</ul>\n<ul>\n<li>Fertility &amp; Family Forming Benefits</li>\n</ul>\n<ul>\n<li>On-demand mental health support and Employee Assistance Program</li>\n</ul>\n<ul>\n<li>Global Travel Medical Insurance</li>\n</ul>\n<p>Financial Benefits</p>\n<ul>\n<li>Short and Long Term Disability Insurance</li>\n</ul>\n<ul>\n<li>Life &amp; Accident Insurance</li>\n</ul>\n<ul>\n<li>401(k) Retirement Savings Plan</li>\n</ul>\n<ul>\n<li>Employee Stock Participation Plan</li>\n</ul>\n<p>Time Off</p>\n<ul>\n<li>Flexible paid time off covering vacation and sick leave</li>\n</ul>\n<ul>\n<li>Leave programs, including parental, pregnancy health, medical, and bereavement leave</li>\n</ul>\n<p>What Makes Cloudflare Special?</p>\n<p>We&#39;re not just a highly ambitious, large-scale technology company. We&#39;re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.</p>\n<p>Project Galileo: Since 2014, we&#39;ve equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare&#39;s enterprise customers--at no cost.</p>\n<p>Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we&#39;ve provided services to more than 425 local government election websites in 33 states.</p>\n<p>1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever built.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_061e824c-343","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cloudflare","sameAs":"https://www.cloudflare.com/","logo":"https://logos.yubhub.co/cloudflare.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/cloudflare/jobs/7088208","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Programming experience in Go, or similar languages","Experience in designing and implementing secure and highly-available distributed systems","Experience (and love) for debugging to ensure the system works in all cases","Experience with a continuous integration workflow and using source control (we use git)","Experience with continuous delivery and deployment of a k8s hosted application","Understanding of security issues and responsibilities","Experience with monitoring, alerting and debugging high volume production systems","Fluent in analyses of data sets such as logs","Strong English language oral and written communications skills","Designing and building APIs","Experience with the Cloudflare development stack is a plus"],"x-skills-preferred":["At least 4 years of hands-on software development experience on meaningfully complex systems","Experience with graph theory and building services for graph generation, storage and retrieval","An understanding of the systems architecture required to scale machine learning model-driven decision engines in a production environment","Experience building both backend systems and frontend widgets","Ability to contribute to planning, development, and execution to meet commitments and deliver with predictability","Experience implementing tools, processes, internal instrumentation, and methodologies","Comfortable working on projects with tight deadlines and short release cycles","Strong verbal and written English language skills","Experience with DCIM, CMDB, IPAM, and other Data Center and Asset Lifecycle Management tools is a plus","Experience with data ingestion and analysis - pulling metrics from hundreds of edge data centers"],"datePosted":"2026-04-18T15:45:07.400Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Hybrid"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Programming experience in Go, or similar languages, Experience in designing and implementing secure and highly-available distributed systems, Experience (and love) for debugging to ensure the system works in all cases, Experience with a continuous integration workflow and using source control (we use git), Experience with continuous delivery and deployment of a k8s hosted application, Understanding of security issues and responsibilities, Experience with monitoring, alerting and debugging high volume production systems, Fluent in analyses of data sets such as logs, Strong English language oral and written communications skills, Designing and building APIs, Experience with the Cloudflare development stack is a plus, At least 4 years of hands-on software development experience on meaningfully complex systems, Experience with graph theory and building services for graph generation, storage and retrieval, An understanding of the systems architecture required to scale machine learning model-driven decision engines in a production environment, Experience building both backend systems and frontend widgets, Ability to contribute to planning, development, and execution to meet commitments and deliver with predictability, Experience implementing tools, processes, internal instrumentation, and methodologies, Comfortable working on projects with tight deadlines and short release cycles, Strong verbal and written English language skills, Experience with DCIM, CMDB, IPAM, and other Data Center and Asset Lifecycle Management tools is a plus, Experience with data ingestion and analysis - pulling metrics from hundreds of edge data centers"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_77ff2013-8f9"},"title":"Senior Product Manager, Context Engineering","description":"<p>ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. As a Senior Product Manager, Context Engineering, you&#39;ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins.</p>\n<p>With tools that amplify your impact and a culture that backs your ambition, you won&#39;t just contribute. You&#39;ll make things happen–fast.</p>\n<p><strong>The Opportunity:</strong></p>\n<p>ZoomInfo built the industry&#39;s most sophisticated GTM data acquisition infrastructure. Now we&#39;re applying that same rigor to context engineering,the emerging discipline that determines whether AI systems deliver transformative value or incremental improvement.</p>\n<p>This role architects the context layer powering our AI intelligence across Copilot, GTM Studio, and MarketingOS. You&#39;ll transform how ZoomInfo&#39;s agentic workflows access, compress, and deliver precisely the right information at exactly the right moment.</p>\n<p>The impact is organization-wide: every AI interaction, every intelligent recommendation, every autonomous agent action depends on the context infrastructure you’ll build.</p>\n<p>We&#39;ve transitioned to AI-first product thinking company-wide. The context pipelines exist but remain nascent,creating a rare opportunity to define architectural patterns and platform standards that compound value across multiple product teams in the years to come.</p>\n<p><strong>What You&#39;ll Do:</strong></p>\n<p>Architect Context Acquisition Pipelines</p>\n<p>Design and optimize how ZoomInfo retrieves, transforms, and delivers context from our semantic data layer, memory systems, and data producers. You&#39;ll balance retrieval quality against latency and cost constraints, implementing hybrid search strategies, intelligent caching, and context compression techniques that maintain information density while respecting token budgets.</p>\n<p>Own the Context Layer Platform</p>\n<p>Build infrastructure serving multiple product teams,Copilot, GTM Studio, MarketingOS,as internal customers. Establish API contracts, developer experience standards, and integration patterns that accelerate feature velocity.</p>\n<p>Maintain the delicate balance between providing flexible building blocks and opinionated solutions that encode best practices.</p>\n<p>Drive Quality Through Measurement</p>\n<p>Implement evaluation frameworks using RAGAS metrics and custom benchmarks. Monitor retrieval precision, context relevance, hallucination rates, and system performance in production.</p>\n<p>Translate quality signals into architectural improvements, working closely with ML engineers to iterate on embedding models, reranking strategies, and retrieval algorithms.</p>\n<p>Navigate Emerging Research</p>\n<p>Context engineering evolves weekly. You&#39;ll continuously evaluate innovations,GraphRAG for multi-hop reasoning, test-time compute scaling, multimodal retrieval, compression techniques,determining which advances warrant production investment versus which remain academic curiosities.</p>\n<p>Bring external best practices to ZoomInfo while contributing learnings back to the broader community.</p>\n<p>Orchestrate Cross-Functional Execution</p>\n<p>Translate between three distinct worlds: ML engineers optimizing retrieval algorithms, platform engineers building scalable infrastructure, and product teams shipping customer features.</p>\n<p>Establish communication cadences, prioritization frameworks, and decision-making processes that balance urgent requests against strategic platform development.</p>\n<p><strong>What You’ll Bring:</strong></p>\n<ul>\n<li>4-6 years of product management experience with 2+ years in ML/AI infrastructure</li>\n</ul>\n<ul>\n<li>Direct experience with production RAG systems, vector databases, or semantic search, context management</li>\n</ul>\n<ul>\n<li>Experience with graph databases (e.g. Neo4j)</li>\n</ul>\n<ul>\n<li>Track record building platform products serving multiple internal or external customers</li>\n</ul>\n<ul>\n<li>Familiarity with context compression, embedding models, and retrieval evaluation frameworks</li>\n</ul>\n<ul>\n<li>History of defining product vision in nascent technical domains where best practices are still emerging</li>\n</ul>\n<p><strong>Who You Are:</strong></p>\n<p>Technical Foundation</p>\n<p>Expert-level understanding of RAG system architecture,you can discuss embedding dimensionality trade-offs, vector database indexing strategies, and reranking approaches with depth.</p>\n<p>You&#39;ve built or significantly contributed to production retrieval systems, not just managed them at arm&#39;s length.</p>\n<p>Python and SQL proficiency enables you to review code, analyze retrieval issues, and prototype solutions for concept validation.</p>\n<p>Platform Product Mindset</p>\n<p>Experience building infrastructure products where internal engineering teams are your customers.</p>\n<p>You measure success through downstream product velocity improvements and developer satisfaction scores, not just uptime metrics.</p>\n<p>You understand platform economics,how each additional team using your infrastructure increases its value through shared learnings and amortized costs.</p>\n<p>Intellectual Velocity</p>\n<p>You read recent research papers from arXiv, ACL, NeurIPS.</p>\n<p>You prototype emerging techniques to understand their practical constraints.</p>\n<p>You maintain strong opinions weakly held, updating your architectural assumptions as evidence accumulates.</p>\n<p>The discipline moves too fast for static expertise,continuous learning is non-negotiable.</p>\n<p>Strategic Communication</p>\n<p>You translate between technical depth and business impact fluently.</p>\n<p>You can explain to executives why implementing GraphRAG takes 6 months but unlocks $10M in product capabilities.</p>\n<p>You can communicate to engineers why business constraints require shipping &#39;good enough&#39; in 3 weeks rather than &#39;optimal&#39; in 3 months.</p>\n<p>You influence without formal authority through data, clear reasoning, and earned credibility.</p>\n<p><strong>The Environment:</strong></p>\n<p>Reporting &amp; Collaboration</p>\n<p>Report to the Senior Product Director for Context Engineering, Semantic Data Layer, and Agentic Memory within ZoomInfo&#39;s Intelligence team.</p>\n<p>Work alongside PMs responsible for signals and ML scoring/recommendation models.</p>\n<p>Together, you ensure our agentic workflows fill context windows with high-quality, information-dense content exactly when needed.</p>\n<p>Pace &amp; Problems</p>\n<p>Fast-moving engineering team that understands the space.</p>\n<p>Company-wide AI adoption push creates both urgency and opportunity.</p>\n<p>Expect interesting problems: How do we maintain sub-200ms retrieval latency at scale?</p>\n<p>When does GraphRAG justify its indexing cost?</p>\n<p>How do we balance context freshness with cache efficiency?</p>\n<p>You&#39;ll shape answers that become architectural patterns across the organization.</p>\n<p>Impact</p>\n<p>Define a nascent discipline at a company that&#39;s already AI-first in product thinking and organizational structure.</p>\n<p>Your architectural decisions compound,every improvement to context quality multiplies across Copilot, GTM Studio, MarketingOS, and future products we haven&#39;t imagined yet.</p>\n<p>This is infrastructure work with direct line-of-sight to customer value.</p>\n<p>#LI-PS1 #LI-remote</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_77ff2013-8f9","directApply":true,"hiringOrganization":{"@type":"Organization","name":"ZoomInfo","sameAs":"https://www.zoominfo.com/","logo":"https://logos.yubhub.co/zoominfo.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/zoominfo/jobs/8206116002","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$89,200-$133,800 USD","x-skills-required":["Product Management","ML/AI Infrastructure","RAG Systems","Vector Databases","Semantic Search","Context Management","Graph Databases","Context Compression","Embedding Models","Retrieval Evaluation Frameworks"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:44:52.232Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Waltham, Massachusetts, United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Product Management, ML/AI Infrastructure, RAG Systems, Vector Databases, Semantic Search, Context Management, Graph Databases, Context Compression, Embedding Models, Retrieval Evaluation Frameworks","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":89200,"maxValue":133800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_deb98db6-eba"},"title":"Staff Software Engineer, Search Quality","description":"<p>At Databricks, we are enabling data teams to solve the world&#39;s toughest problems by building and running the world&#39;s best data and AI infrastructure platform.来たSearch plays a foundational role in this mission, powering everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration.</p>\n<p>As a Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks&#39; 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This is a critical role, as Consultants have an amazing chance to make an immediate impact on the success of Elastic and our customers.</p>\n<p>Given the opportunity and the organisations that you will be working with, you must be a current holder of Security clearance.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Strong customer advocacy, relationship building, and communications skills</li>\n<li>The ability to easily pivot from delivery to strategic engagements with customers</li>\n<li>To work with the wider Elastic organisation to support the customer’s goals, their strategic requirements and their journey with Elastic.</li>\n<li>Ownership of the strategic roadmap with the customer including quarterly strategic sessions with senior and key stakeholders either in one or a number of customers with common goals.</li>\n<li>Solution design, development, and integration of Elastic products and APIs, platform architecture, and capacity planning in mission-critical environments</li>\n<li>Comfortable working remotely in a highly distributed team</li>\n<li>Development of demos and proof-of-concepts that highlight the value of the Elastic Stack</li>\n<li>Data modelling, query development and optimisation, cluster tuning and scaling with a focus on fast search and analytics at scale</li>\n<li>Solving our customers’ most challenging data problems</li>\n<li>Working closely with the Elastic engineering, product management, and support teams to identify feature enhancements, extensions.</li>\n<li>Engaging with the Elastic Sales team to scope opportunities while assessing technical risks, questions, or concerns</li>\n</ul>\n<p>What You Bring Along:</p>\n<ul>\n<li>Hands-on experience and an understanding of Elasticsearch and/or Lucene</li>\n<li>Minimum of 2 years’ experience as a Software Engineer, System Administrator, or DevOps Engineer</li>\n<li>Minimum of 5 years&#39; experience working as a Consultant, working to deliver and execute on professional services engagements</li>\n<li>Currently holding security clearance</li>\n<li>Experience as a technical instructor or public speaker to large audiences on enterprise infrastructure software technology to engineers, developers, and other technical positions</li>\n<li>Excel at working directly with customers to gather, prioritise, plan and execute solutions to customer business requirements as it relates to our technologies</li>\n<li>Understanding and passion for open-source technology and knowledge and proficient in at least one programming language</li>\n<li>Hands-on experience with large distributed systems from an architecture and development perspective</li>\n<li>Knowledge of information retrieval and/or analytics domain</li>\n<li>The nature of the work that you will be doing will require a high percentage of work onsite with customers, and you should be expected to travel as a result of this requirement</li>\n<li>Understanding of Linux, Java and databases</li>\n</ul>\n<p>Bonus Points:</p>\n<ul>\n<li>Deep understanding of Elasticsearch and Lucene, including Elastic Certified Engineer certification</li>\n<li>BS, MS or PhD in Computer Science or related engineering discipline</li>\n<li>Strong knowledge of Java and Linux/Unix environment, software development, and/or experience with distributed systems</li>\n<li>Experience and interest in delivering and/or developing product training</li>\n<li>Experience contributing to an open-source project or documentation</li>\n</ul>\n<p>As a distributed company, diversity drives our identity. 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We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.</p>\n<p>Competitive pay based on the work you do here and not your previous salary Health coverage for you and your family in many locations Ability to craft your calendar with flexible locations and schedules for many roles Generous number of vacation days each year Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service Up to 40 hours each year to use toward volunteer projects you love Embracing parenthood with minimum of 16 weeks of parental leave</p>\n<p>Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. 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You&#39;ll own the backend infrastructure that makes our content discoverable, our features responsive, and our platform reliable at scale.</p>\n<p>Your work will directly shape what users experience: designing APIs that serve rich content, building services that handle real-time interactions, implementing content-matching systems for rights and safety, and ensuring our platform performs under load. You&#39;ll architect systems that are fast, correct, and maintainable.</p>\n<p>You&#39;ll collaborate closely with Product, ML Research, and Mobile/Web teams to ship features that matter. We use Python, Go, BigQuery, Pub/Sub, and a microservices architecture,but we care more about good judgment than specific tool experience.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design and maintain application-level data models that organize rich content into canonical structures optimized for product features, search, and retrieval.</li>\n<li>Build high-reliability ETLs and streaming pipelines to process usage events, analytics data, behavioral signals, and application logs.</li>\n<li>Develop data services that expose unified content to the application, such as metadata access APIs, indexing workflows, and retrieval-ready representations.</li>\n<li>Implement and refine fingerprinting pipelines used for deduplication, rights attribution, safety checks, and provenance validation.</li>\n<li>Own data consistency between ingestion systems, application surfaces, metadata storage, and downstream reporting environments.</li>\n<li>Define and track key operational metrics, including latency, completeness, accuracy, and event health.</li>\n<li>Collaborate with Product teams to ensure content structures and APIs support evolving features and high-quality user experiences.</li>\n<li>Partner with Analytics and Research teams to deliver clean usage datasets for experimentation, model evaluation, reporting, and internal insights.</li>\n<li>Operate large analytical workloads in BigQuery and build reusable Dataflow/Beam components for structured processing.</li>\n<li>Improve reliability and scale by designing robust schema evolution strategies, idempotent pipelines, and well-instrumented operational flows.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Experience building production backend services and APIs at scale</li>\n<li>Experience building ETL/ELT pipelines, event processing systems, and structured data models for applications or analytics</li>\n<li>Strong background in data modeling, metadata systems, indexing, or building canonical representations for heterogeneous content</li>\n<li>Proficiency in Python, Go, SQL, and scalable data-processing frameworks (Dataflow/Beam, Spark, or similar)</li>\n<li>Familiarity with BigQuery or other analytical data warehouses and strong comfort optimizing large queries and schemas</li>\n<li>Experience with event-driven architectures, Pub/Sub, or Kafka-like systems</li>\n<li>Strong understanding of data quality, schema evolution, lineage, and operational reliability</li>\n<li>Ability to design pipelines that balance cost, latency, correctness, and scale</li>\n<li>Clear communication skills and an ability to collaborate closely with Product, Research, and Analytics stakeholders</li>\n</ul>\n<p><strong>Nice to Have</strong></p>\n<ul>\n<li>Experience building application-facing APIs or microservices that expose structured content</li>\n<li>Background in information retrieval, indexing systems, or search infrastructure</li>\n<li>Experience with fingerprinting, perceptual hashing, audio similarity metrics, or content-matching algorithms</li>\n<li>Familiarity with ML workflows and how downstream analytics and usage data feed back into research pipelines</li>\n<li>Understanding of batch + streaming architectures and how to blend them effectively</li>\n<li>Experience with Go, Next.js, or React Native for occasional full-stack contributions</li>\n</ul>\n<p><strong>Why Join Us</strong></p>\n<p>You will design the core data services and pipelines that power our product experience, analytics, and business operations. You’ll work on high-impact data challenges involving real-time signals, large-scale metadata systems, and cross-platform consistency. You’ll join a small, fast-moving team where you’ll shape the structure, reliability, and intelligence of our downstream data ecosystem.</p>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Highly competitive salary and equity</li>\n<li>Quarterly productivity budget</li>\n<li>Flexible time off</li>\n<li>Fantastic office location in Manhattan</li>\n<li>Productivity package, including ChatGPT Plus, Claude Code, and Copilot</li>\n<li>Top-notch private health, dental, and vision insurance for you and your dependents</li>\n<li>401(k) plan options with employer matching</li>\n<li>Concierge medical/primary care through One Medical and Rightway</li>\n<li>Mental health support from Spring Health</li>\n<li>Personalized life insurance, travel assistance, and many other perks</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ceba9e5b-250","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Udio","sameAs":"https://www.udio.com/","logo":"https://logos.yubhub.co/udio.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/udio/jobs/4987729008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$180,000 - $220,000","x-skills-required":["Python","Go","BigQuery","Pub/Sub","Data modeling","Metadata systems","Indexing","Canonical representations","ETL/ELT pipelines","Event processing systems","Structured data models","Scalable data-processing frameworks","Analytical data warehouses","Event-driven architectures","Kafka-like systems","Data quality","Schema evolution","Lineage","Operational reliability"],"x-skills-preferred":["Application-facing APIs","Microservices","Information retrieval","Indexing systems","Search infrastructure","Fingerprinting","Perceptual hashing","Audio similarity metrics","Content-matching algorithms","ML workflows","Batch + streaming architectures"],"datePosted":"2026-04-17T13:05:20.076Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Go, BigQuery, Pub/Sub, Data modeling, Metadata systems, Indexing, Canonical representations, ETL/ELT pipelines, Event processing systems, Structured data models, Scalable data-processing frameworks, Analytical data warehouses, Event-driven architectures, Kafka-like systems, Data quality, Schema evolution, Lineage, Operational reliability, Application-facing APIs, Microservices, Information retrieval, Indexing systems, Search infrastructure, Fingerprinting, Perceptual hashing, Audio similarity metrics, Content-matching algorithms, ML workflows, Batch + streaming architectures","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":220000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4d14bef3-77e"},"title":"Staff Software Engineer - AI Applications","description":"<p>We believe that the way people interact with their finances will drastically improve in the next few years. We&#39;re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life.</p>\n<p>We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid&#39;s network covers 12,000 financial institutions across the US, Canada, UK and Europe.</p>\n<p>The AI Applications Team You will have the opportunity to join as one of the founding members of this newly formed team that is dedicated to consolidating and rapidly scaling our successful bets so far, and grow with the team in our quest to accelerate Plaid&#39;s transformation into an AI-first company.</p>\n<p>In this role you will lead projects that enable and scale our business with our largest AI customers and partners, starting with personal finance use cases and expanding into many others; examples include:</p>\n<ul>\n<li>Develop and evolve the preferred integration pattern for Plaid with AI providers - from API adaptations to building the official Plaid MCP Servers, and beyond</li>\n</ul>\n<ul>\n<li>Redefine how Plaid&#39;s consumer link experience embed into conversational interfaces in the most seamless way</li>\n</ul>\n<ul>\n<li>Architect the trust layer for the future of agentic commerce that will become the industry standard</li>\n</ul>\n<p>Additionally you will be expected to scale and extend our existing successful bets on AI-powered customer experience; examples include:</p>\n<ul>\n<li>Make the next step-function improvement in our homegrown customer support agent</li>\n</ul>\n<ul>\n<li>Land our multi-turn and multi-agent system that powers a truly delightful experience for our customers; define how to scalably run offline evaluation for complex multi-turn open-ended tasks; research and prototype how Human-In-The-Loop - Reinforcement Learning (RLHF) can power an insights flywheel; pioneer the architecture for customer-specific long-term memory, etc.</li>\n</ul>\n<ul>\n<li>Extend our agentic system to support other critical parts of the customer journey, starting with areas with the highest ROI - top-of-funnel product recommendation, customer onboarding and risk diligence, customer activation and assistance for faster productionization, as well as upselling and cross-selling of Plaid products</li>\n</ul>\n<p>You will have a front row seat to all the latest industry developments. Over time, with the skills and experience you develop and hone on this team, you can become an influential voice in defining where AI &lt; Fintech will be heading longer term.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Build across the stack. Design, develop, and maintain scalable backend services and APIs, as well as intuitive, high-quality frontend applications that bring those systems to life.</li>\n</ul>\n<ul>\n<li>Work with other AI engineers, software engineers and machine learning engineers to architect, design and implement GenAI-powered products and features</li>\n</ul>\n<ul>\n<li>Collaborate across functions to understand user needs, propose and implement AI-powered solutions where they’re expected to have the highest impact</li>\n</ul>\n<ul>\n<li>Design and execute rapid experiments to push the boundaries on potential business impact from emerging AI capabilities, with a focus on minimal viable testing approaches</li>\n</ul>\n<ul>\n<li>Balance creative exploration of possibilities with rigorous evaluation of technical feasibility, product potential and business impact</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Experience building backend services and working with microservices or service-oriented architectures</li>\n</ul>\n<ul>\n<li>Strong working knowledge of HTML, CSS, JavaScript, and modern frontend frameworks or libraries, with comfort building user-facing experiences</li>\n</ul>\n<ul>\n<li>Hands-on experience working with LLMs to build products and shipping them to product with iterating with real user feedback - including but not limited to:</li>\n</ul>\n<ul>\n<li>Prompt engineering</li>\n</ul>\n<ul>\n<li>Fine-tuning</li>\n</ul>\n<ul>\n<li>Retrieval augmented generation (RAG)</li>\n</ul>\n<ul>\n<li>Semantic search</li>\n</ul>\n<ul>\n<li>Vector database and embedding models</li>\n</ul>\n<ul>\n<li>Agent orchestration framework</li>\n</ul>\n<ul>\n<li>Evaluation and monitoring framework of open-ended tasks</li>\n</ul>\n<ul>\n<li>Streaming and SSE</li>\n</ul>\n<ul>\n<li>Common UX and design patterns for GenAI-powered products</li>\n</ul>\n<ul>\n<li>Strong debugging and monitoring experience for production systems</li>\n</ul>\n<ul>\n<li>Ability to deeply understand customer and user needs through user research and rapid experimentation - be your own technical PM</li>\n</ul>\n<ul>\n<li>Ability to balance divergent thinking (exploring possibilities) with convergent thinking (evaluating feasibility), which is critical for driving 0 -&gt;1 projects</li>\n</ul>\n<ul>\n<li>Extremely curious and passionate about working in GenAI applications space</li>\n</ul>\n<p><strong>Nice-to-Haves</strong></p>\n<ul>\n<li>Experience training and/or serving ML models in production, or fine-tuning LLMs for domain-specific use cases</li>\n</ul>\n<ul>\n<li>Comfortable operating in privacy/PII-sensitive environments and applying compliance mitigations</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_4d14bef3-77e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Plaid","sameAs":"https://plaid.com/","logo":"https://logos.yubhub.co/plaid.com.png"},"x-apply-url":"https://jobs.lever.co/plaid/a6bf6eeb-6486-4e45-a3b2-e712f32523d3","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$228,360-$369,800 per year","x-skills-required":["backend services","microservices","service-oriented architectures","HTML","CSS","JavaScript","modern frontend frameworks","LLMs","prompt engineering","fine-tuning","retrieval augmented generation","semantic search","vector database","embedding models","agent orchestration framework","evaluation and monitoring framework","streaming","SSE","UX and design patterns","debugging","monitoring"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:55:58.129Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"backend services, microservices, service-oriented architectures, HTML, CSS, JavaScript, modern frontend frameworks, LLMs, prompt engineering, fine-tuning, retrieval augmented generation, semantic search, vector database, embedding models, agent orchestration framework, evaluation and monitoring framework, streaming, SSE, UX and design patterns, debugging, monitoring","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":228360,"maxValue":369800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c6ad7239-e8e"},"title":"Technical Support Engineer","description":"<p>At Eve, we&#39;re redefining what&#39;s possible in legal technology. Our mission is to empower plaintiff law firms with AI-driven solutions that elevate how they operate, serve clients, and grow.</p>\n<p>We believe the future of law will be built by &#39;AI-Native Law Firms&#39; , firms that are managed, scaled, and optimized by intelligent systems rather than manual processes and endless administrative work.</p>\n<p>Eve&#39;s technology augments the capabilities of attorneys across every stage of a case , from intake and document review to strategy and settlement , so they can focus on what truly matters: achieving the best outcomes for their clients.</p>\n<p>Our vision is simple yet transformative: enable every firm to operate at its highest potential through the power of AI.</p>\n<p><strong>Why Join Eve:</strong></p>\n<p>This is not a traditional support role. Eve&#39;s Technical Support Engineers are technical problem solvers who work at the intersection of a cutting-edge AI product and the 850+ plaintiff law firms that depend on it.</p>\n<p>When a paralegal reports that a medical chronology &#39;doesn&#39;t look right,&#39; your job is to determine whether that&#39;s a retrieval issue, a data ingestion problem, a model behavior question, or user error.</p>\n<p>You&#39;ll investigate using AI observability tooling, document your findings with precision, and either resolve the issue or hand engineering a complete diagnostic they can act on immediately.</p>\n<p>A significant portion of this role involves investigating AI output quality , understanding why the product generated what it did and whether the result is correct, incomplete, or wrong.</p>\n<p>The rest is split between diagnosing traditional technical issues (document formatting, cloud storage sync, integrations) and building the support infrastructure itself: writing SOPs, expanding the knowledge base, and helping shape our AI agent rollout.</p>\n<p><strong>What You Will Accomplish:</strong></p>\n<ul>\n<li>Investigate AI Output Quality: When customers report issues with AI-generated legal documents, you investigate.</li>\n</ul>\n<p>You&#39;ll use AI observability tooling to trace model inputs, outputs, and reasoning.</p>\n<p>You&#39;ll verify claims against source documents and determine whether the issue is a retrieval failure, a data ingestion problem, a prompt issue, or expected model behavior.</p>\n<p>You clearly communicate your findings to non-technical legal professionals.</p>\n<ul>\n<li>Diagnose Technical Issues: Troubleshoot cloud storage sync failures (SharePoint, OneDrive, Dropbox), document formatting and export issues, file handling errors, integration configuration problems, and processing performance issues.</li>\n</ul>\n<p>Resolve what you can independently and escalate what you can&#39;t with full diagnostic evidence.</p>\n<ul>\n<li>Deliver Engineering-Ready Escalations: Every escalation you send to engineering includes an issue summary, trace logs, verified reproduction steps, document context, and business impact assessment.</li>\n</ul>\n<p>You set the quality bar for how support communicates with engineering.</p>\n<ul>\n<li>Operate with Speed: Respond to customer support tickets within SLA.</li>\n</ul>\n<p>Prioritize ruthlessly.</p>\n<p>Manage multiple threads without dropping context.</p>\n<ul>\n<li>Build the Support Infrastructure: Write SOPs, troubleshooting runbooks, and knowledge base articles.</li>\n</ul>\n<p>Contribute to our AI agent rollout by optimizing content for AI consumption.</p>\n<p>Help build the onboarding program for future support engineers.</p>\n<p>You are joining a team that is actively building its processes, not maintaining them.</p>\n<ul>\n<li>Build with AI: Use AI tools daily to accelerate support workflows , drafting responses, analyzing ticket patterns, and diagnosing product behavior.</li>\n</ul>\n<p>Help shape how Eve deploys AI agents for first-touch triage and self-service resolution.</p>\n<p>Define what AI-native support looks like in legal tech.</p>\n<p><strong>What We Are Looking For:</strong></p>\n<ul>\n<li>AI Debugging Ability: You can investigate why an AI-generated document produced an unexpected result.</li>\n</ul>\n<p>You&#39;re comfortable navigating AI observability and tracing tooling to understand model behavior.</p>\n<p>You can distinguish between a retrieval failure, a prompt issue, and a data ingestion problem , and explain the difference to a paralegal.</p>\n<ul>\n<li>Technical Depth: You can read logs, trace API calls, debug OAuth token expirations, diagnose cloud storage sync failures, and reason about what&#39;s happening under the hood of a SaaS product.</li>\n</ul>\n<p>You don&#39;t need to be a software engineer, but you think like one when troubleshooting.</p>\n<ul>\n<li>Structured Escalation Discipline: You document your work with precision.</li>\n</ul>\n<p>Your bug reports include trace logs, reproduction steps, relevant context, and a clear classification of the issue type.</p>\n<p>Engineering can pick up your escalation and start working immediately without asking follow-up questions.</p>\n<ul>\n<li>Exceptional Communication: You can explain complex technical and AI-specific issues to attorneys who don&#39;t care about your stack.</li>\n</ul>\n<p>You write clearly, concisely, and with empathy.</p>\n<p>You know when to simplify and when to be precise.</p>\n<ul>\n<li>Ownership Mentality: You take personal responsibility for customer outcomes.</li>\n</ul>\n<p>You follow through until the problem is solved, not just escalated.</p>\n<p>You don&#39;t wait to be told what to do.</p>\n<p><strong>You Will Thrive in This Role If You Have:</strong></p>\n<ul>\n<li>3+ years in a technical support, support engineering, or technical customer-facing role at a SaaS company</li>\n</ul>\n<p>Experience supporting AI-powered or ML-driven products, with exposure to LLM observability or evaluation platforms</p>\n<p>Background in legal technology, law firm IT operations, or professional services software</p>\n<p>Familiarity with APIs, webhooks, OAuth, and integration debugging , especially cloud storage integrations (SharePoint, OneDrive, Dropbox)</p>\n<p>Experience writing scripts (Python, JS) to automate support workflows or analyze data</p>\n<p>Comfort with SQL for querying logs or data analysis</p>\n<p>Understanding of prompt engineering concepts, retrieval-augmented generation (RAG), and LLM behavior patterns</p>\n<p>History of contributing to SOPs, runbooks, knowledge bases, or internal tooling that materially improved team performance</p>\n<p>Ability to work independently in a remote environment while collaborating effectively across team</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c6ad7239-e8e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Eve","sameAs":"https://www.eve.com/","logo":"https://logos.yubhub.co/eve.com.png"},"x-apply-url":"https://jobs.lever.co/Eve/8ee47c51-3480-4af6-8ab7-d8f22b7922e2","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI Debugging","Technical Support","Cloud Storage Integrations","APIs","Webhooks","OAuth","Integration Debugging","SQL","Prompt Engineering","Retrieval-Augmented Generation","LLM Behavior Patterns"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:31:21.689Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI Debugging, Technical Support, Cloud Storage Integrations, APIs, Webhooks, OAuth, Integration Debugging, SQL, Prompt Engineering, Retrieval-Augmented Generation, LLM Behavior Patterns"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c63160d7-3af"},"title":"Senior Machine Learning Engineer","description":"<p>Join us on this thrilling journey to revolutionize the workforce with AI. As a Senior Machine Learning Engineer at Cresta, you will play a key role in shaping the future of work.</p>\n<p>At Cresta, we are on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioural best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster.</p>\n<p>As a Senior Machine Learning Engineer, you will lead the design and development of Cresta&#39;s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches. You will architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead the design and development of Cresta&#39;s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.</li>\n<li>Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.</li>\n<li>Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.</li>\n<li>Improve reasoning, planning, and tool-use capabilities in real-world AI applications.</li>\n<li>Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.</li>\n<li>Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.</li>\n<li>Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.</li>\n<li>Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.</li>\n<li>Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta&#39;s platform.</li>\n<li>Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta&#39;s AI systems.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Bachelor&#39;s degree in Computer Science, Mathematics, or a related field; Master&#39;s or Ph.D. preferred.</li>\n<li>5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.</li>\n<li>Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.</li>\n<li>Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.</li>\n<li>Experience building and evaluating complex agentic or multi-step LLM workflows.</li>\n<li>Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.</li>\n<li>Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.</li>\n<li>Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.</li>\n</ul>\n<p>Perks &amp; Benefits:</p>\n<ul>\n<li>We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family&#39;s needs.</li>\n<li>Paid parental leave to support you and your family.</li>\n<li>Monthly Health &amp; Wellness allowance.</li>\n<li>Work from home office stipend to help you succeed in a remote environment.</li>\n<li>Lunch reimbursement for in-office employees.</li>\n<li>PTO: 3 weeks in Canada.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c63160d7-3af","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cresta","sameAs":"https://www.cresta.ai/","logo":"https://logos.yubhub.co/cresta.ai.png"},"x-apply-url":"https://job-boards.greenhouse.io/cresta/jobs/4249943008","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["NLP","Generative AI","Transformer architectures","Embeddings","Retrieval systems","PyTorch","TensorFlow","Hugging Face","Distributed/cloud-based infrastructure"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:27:30.020Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Canada (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"NLP, Generative AI, Transformer architectures, Embeddings, Retrieval systems, PyTorch, TensorFlow, Hugging Face, Distributed/cloud-based infrastructure"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8db20763-21b"},"title":"AI Product Owner - Operations","description":"<p>The Role</p>\n<p>Belong is building the Residential Operating System: a fully integrated, AI-powered platform that manages homes, coordinates thousands of real-world service moments, and creates authentic belonging experiences for homeowners and residents. The member journey is the product. But the Residential OS only delivers on that promise if the operational machinery running beneath it is intelligent, instrumented, and self-improving.</p>\n<p>Most companies say they are AI-first. At Belong, it means something specific: by the end of 2025, the majority of communications across sales, leasing, homecare, and concierge functions are AI-generated. Human Advisors and Concierges handle trust-critical moments. AI agents handle everything else: triage, scheduling, status updates, escalation routing, vendor coordination, documentation.</p>\n<p>The operations product surface is where that architecture lives or dies. As Product Owner, Operations, your job is to design, deploy, and relentlessly improve the AI-powered system that runs the homeowner and resident journey from inspection through occupancy. You are not writing requirements for a future that engineers will build someday. You are shipping agent-driven workflows today, measuring their quality and deflection rates next week, and iterating the week after.</p>\n<p>This role is for someone who understands that the frontier of operations is not better dashboards. It is autonomous systems that perform with the judgment of your best operator, at infinite scale, at the moment the member needs it.</p>\n<p>Responsibilities</p>\n<ul>\n<li><p>AI agent architecture across the operational journey. Every operational phase, from home preparation, move-in orchestration, homecare and maintenance, to Pro coordination and vendor scheduling, has a human workflow today and an AI-assisted target state. You will define that target state phase by phase: what the agent handles autonomously, what triggers human review, what escalates immediately.</p>\n</li>\n<li><p>The agent-human handoff model. The Member Journey Brief is explicit: humans are deployed at trust-critical moments. AI handles orchestration, speed, and precision behind the scenes. You are the person who defines exactly where that line sits, and who moves it systematically as agent quality improves.</p>\n</li>\n<li><p>LLM-powered communication workflows. Belong&#39;s target is 80% AI-generated communications across operational functions by Q3. You will own the product layer that makes this real for operations: the prompt architecture, context retrieval pipelines, output quality review systems, and the feedback loops that improve generation quality over time.</p>\n</li>\n<li><p>Foundation as the AI control panel. Foundation is where Belong&#39;s operational teams live. Every tool your squad ships into Foundation is either creating leverage for humans or replacing manual work with agent-driven automation. You will define the roadmap for Foundation&#39;s evolution from task management system to AI control panel: where agents surface for review, where exceptions queue for human action, where quality scores and deflection rates are visible in real time.</p>\n</li>\n<li><p>Operational instrumentation and model feedback. AI systems degrade without structured feedback. You will build the instrumentation that captures ground truth: CSAT signals, escalation rates, rework rates, SLA breach patterns, and member sentiment. You will design the feedback loops that push this signal back into model evaluation and prompt improvement.</p>\n</li>\n</ul>\n<p>The AI Stack You Will Work With</p>\n<ul>\n<li>LLM-based communication generation with context injection from CRM and operational state</li>\n<li>Agentic scheduling and coordination workflows (Homecare triage, Pro dispatch, vendor coordination)</li>\n<li>Automated escalation routing based on signal classification</li>\n<li>Quality scoring and anomaly detection on agent outputs</li>\n<li>Retrieval-augmented generation for Concierge and Homecare agent context</li>\n</ul>\n<p>What Success Looks Like</p>\n<ul>\n<li>90 days: Every operational phase has a documented AI target state with defined autonomous scope, human escalation thresholds, and instrumentation in place.</li>\n<li>6 months: AI-assisted workflows have measurably reduced manual communication volume across at least 2 operational functions with no CSAT degradation.</li>\n<li>Year 1: The majority of routine operational communications in your product surface are AI-generated. Human operators are handling exceptions, escalations, and trust-critical moments, nothing else.</li>\n</ul>\n<p>Example KPIs You Will Be Held To</p>\n<ul>\n<li>AI deflection rate vs. manual handling baseline, by operational function</li>\n<li>CSAT from homeowners and residents at each operational phase (the constraint: deflection gains cannot come at CSAT cost)</li>\n<li>SLA compliance rates for homecare and Pro services</li>\n<li>Time-to-list (inspection to live listing)</li>\n<li>Move-in readiness rate and failed move-in rate</li>\n<li>Human escalation rate as a quality signal on agent confidence calibration</li>\n</ul>\n<p>Who You Are</p>\n<ul>\n<li>AI systems thinker. You do not think about AI features. You think about AI systems: input context, output quality, fallback behavior, quality measurement, and continuous improvement loops.</li>\n<li>Operationally grounded. You have worked in environments where things break in the real world, with real vendors, real homes, real members, and you understand that an agent operating without the right context is more dangerous than no agent at all.</li>\n<li>Outcome obsessed. You hold deflection rate and CSAT simultaneously. You do not celebrate automation that degrades experience.</li>\n<li>Technically fluent. You can write a SQL query, read a vector similarity result, reason about retrieval quality, and understand the tradeoffs in a prompt engineering decision.</li>\n<li>Cross-functional driver. Operations, Homecare, Leasing, Vendor Ops, and Engineering all touch your surface. You run the rituals, translate across languages, and hold the delivery cadence.</li>\n</ul>\n<p>What You Bring</p>\n<ul>\n<li>3 to 5 years of product experience, with at least 1 to 2 years directly building or operating AI-powered products in a production environment</li>\n<li>Hands-on experience with LLM integrations, prompt engineering, RAG pipelines, or agentic workflow design</li>\n<li>Demonstrated ownership of operational tooling or service orchestration products in a marketplace, logistics, or operations-intensive environment</li>\n<li>Proficiency with data: SQL, funnel analysis, and the ability to detect when a metric is being gamed or misread</li>\n<li>Experience with AI evaluation frameworks and output quality measurement is a strong advantage</li>\n<li>Prior work in consumer real estate, hospitality, or residential services is a plus</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8db20763-21b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Belong","sameAs":"https://www.belong.com/","logo":"https://logos.yubhub.co/belong.com.png"},"x-apply-url":"https://jobs.lever.co/belong/12878464-3397-4603-91fd-a4645ee06afe","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI systems thinking","LLM-powered workflows","Agentic scheduling and coordination workflows","Automated escalation routing","Quality scoring and anomaly detection","Retrieval-augmented generation","SQL","Funnel analysis","Data analysis","Prompt engineering","RAG pipelines","Agentic workflow design","Operational tooling","Service orchestration","Consumer real estate","Hospitality","Residential services"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:27:01.211Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Argentina"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI systems thinking, LLM-powered workflows, Agentic scheduling and coordination workflows, Automated escalation routing, Quality scoring and anomaly detection, Retrieval-augmented generation, SQL, Funnel analysis, Data analysis, Prompt engineering, RAG pipelines, Agentic workflow design, Operational tooling, Service orchestration, Consumer real estate, Hospitality, Residential services"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cc051e9f-7ab"},"title":"AI Product Owner - Growth","description":"<p>The Role ================ Product Owner, Growth (AI-First) The Role Belongs growth constraint is supply. Every homeowner who activates on the platform adds a home to the network, creates a resident opportunity, and moves Belong closer to the profitability inflection that defines the next chapter of the company.</p>\n<p>The homeowner funnel, from first impression through signed agreement and activated listing, is the highest-leverage product surface in the business. Most growth product roles are about optimizing what already exists: faster page loads, shorter forms, better copy. This role is about building something structurally different.</p>\n<p>Belong&#39;s homeowner acquisition funnel is being rebuilt as an AI-native system: conversational intake powered by LLMs, personalized onboarding that adapts dynamically to each homeowner&#39;s financial profile, predictive scoring that routes the right lead to the right moment in the Advisor workflow, and agentic follow-up that replaces manual sequences with intelligent, context-aware outreach.</p>\n<p>The target is a funnel that learns, where every interaction generates signal that makes the next interaction more likely to convert. As Product Owner, Growth, you are the person building that system. You own the homeowner acquisition and activation funnel end to end, from first contact to listed home.</p>\n<p>Responsibilities ================</p>\n<p><strong>AI-native intake and qualification layer</strong></p>\n<p>The first interaction a homeowner has with Belong, whether via belonghome.com, a paid channel, or a referral, is where trust is either established or lost. You will build conversational intake flows powered by LLMs that qualify, capture, and begin converting leads in real time.</p>\n<p>These are not chatbots with decision trees. They are context-aware systems that understand the difference between a cashflow-positive homeowner who wants yield optimization and a cashflow-negative homeowner who needs a path to profitability, and adapt the conversation, the framing, and the call-to-action accordingly.</p>\n<p><strong>Personalized onboarding and trust architecture</strong></p>\n<p>A homeowner considering Belong is anxious. They are considering handing over their most valuable asset to a platform they found online. Conversion at this stage is not a UX problem. It is a trust architecture problem.</p>\n<p>You will design onboarding sequences that adapt dynamically based on homeowner attributes: property type, cashflow profile, prior rental history, risk signals, and behavioral signals from in-session activity.</p>\n<p>You will use LLMs to generate personalized content, market analyses, improvement ROI estimates, comparable listings, that makes the value proposition concrete and specific to their home, not generic.</p>\n<p><strong>Predictive lead scoring and Advisor routing</strong></p>\n<p>Belong&#39;s Advisors are the trust-critical human touchpoint in the homeowner funnel. Their time is finite and high-value. You will build the predictive infrastructure that scores every lead on conversion likelihood, property quality, and fit with Belong&#39;s ICP, and routes leads to Advisors with the context they need to have the right conversation immediately.</p>\n<p>You will work with data science to train and evaluate these models, with RevOps to deploy them into the Salesforce workflow, and with Sales leadership to validate signal quality against actual close rates.</p>\n<p><strong>Agentic follow-up and nurture sequences</strong></p>\n<p>Most leads do not convert on the first contact. Today, nurture is a sequence of templated emails. The target state is an AI agent that monitors lead behavior, page views, document opens, return visits, session signals, and generates contextually appropriate, personalized outreach at the right moment, with the right frame, without a human initiating every touchpoint.</p>\n<p>You will define the agent&#39;s decision logic, build the context retrieval pipeline, instrument the output quality, and iterate on conversion impact week over week.</p>\n<p><strong>Funnel instrumentation and the learning loop</strong></p>\n<p>An AI-native funnel without rigorous instrumentation is a black box. You will build the measurement architecture that makes every conversion decision traceable: which intake flow variant produced the lead, which scoring model routed it, which agent-generated touchpoint influenced the next action, which Advisor framing closed it.</p>\n<p>You will design the feedback loops that push conversion signal back into model evaluation, prompt improvement, and scoring recalibration. The funnel gets smarter every week or it is not an AI-native funnel.</p>\n<p><strong>The activation gap: agreement to listed home</strong></p>\n<p>Signing the agreement is not growth. A listed home is growth. The conversion from signed agreement to activated listing is a product problem with high leverage: homeowners who do not complete inspection scheduling, who abandon the improvement process, or who sit in the pipeline without a live listing represent real lost revenue.</p>\n<p>You will own the product layer that closes this gap, including AI-assisted improvement planning, proactive homeowner communication anchored to their cashflow profile, and predictive identification of homeowners at risk of churning before listing.</p>\n<p>The AI Stack You Will Work With ===========================</p>\n<ul>\n<li>LLM-powered conversational intake with real-time lead qualification and cashflow profile detection</li>\n<li>Personalized content generation using property-level market data, comparable listings, and improvement ROI modeling</li>\n<li>Predictive lead scoring models trained on conversion, property quality, and ICP signals</li>\n<li>Agentic follow-up workflows with behavioral trigger logic and context-aware generation</li>\n<li>Retrieval-augmented generation for Advisor preparation: the right context, surfaced at the right moment before the call</li>\n<li>A/B testing infrastructure applied to AI-generated content variants, not just static copy</li>\n</ul>\n<p>What Success Looks Like ====================== 90 days: The funnel is fully instrumented from first click to activated listing with conversion rates and drop-off points visible at each stage. An AI-assisted intake flow is in production and being tested against the baseline.</p>\n<p>6 months: Lead-to-listing conversion is measurably above baseline. AI is integrated at a minimum of 3 funnel touchpoints with documented conversion impact per touchpoint. Advisor routing is scored, and the correlation between score and close rate is being tracked.</p>\n<p>Year 1: The majority of homeowner outreach between first contact and agreement signing is AI-generated, with human Advisors focusing exclusively on trust-critical call moments. CAC on the supply side is trending down. Time-to-activation is compressing quarter over quarter.</p>\n<p>Example KPIs You Will Be Held To ==================================</p>\n<ul>\n<li>Lead-to-listing conversion rate (the primary number)</li>\n<li>Cost per activated listing</li>\n<li>Time from first contact to listing live</li>\n<li>AI-assisted funnel touchpoint conversion impact, measured per touchpoint</li>\n<li>Advisor routing accuracy: scored lead close rate vs. unscored baseline</li>\n<li>Experiment velocity: instrumented tests shipped per month</li>\n<li>Homeowner CSAT at onboarding and inspection phases (the constraint: conversion gains cannot come at experience cost)</li>\n</ul>\n<p>Who You Are ============ AI systems builder, not AI enthusiast. You have shipped LLM-powered product features in production. You understand prompt engineering, retrieval quality, latency tradeoffs, output evaluation, and model feedback loops. You think about AI systems the way a statistician thinks about models: with explicit assumptions, known failure modes</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_cc051e9f-7ab","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Belong","sameAs":"https://www.belonghome.com/","logo":"https://logos.yubhub.co/belonghome.com.png"},"x-apply-url":"https://jobs.lever.co/belong/0360a259-aa2d-492a-9c20-33497533573e","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["LLM-powered conversational intake","Personalized content generation","Predictive lead scoring models","Agentic follow-up workflows","Retrieval-augmented generation","A/B testing infrastructure"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:26:43.650Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Argentina"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLM-powered conversational intake, Personalized content generation, Predictive lead scoring models, Agentic follow-up workflows, Retrieval-augmented generation, A/B testing infrastructure"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e5ecff17-84f"},"title":"Senior Forward Deployed Engineer (AI Agent) - UK","description":"<p>Join us on this thrilling journey to revolutionise the workforce with AI.</p>\n<p>The AI Agent team at Cresta is on a mission to create state-of-the-art AI Agents that solve practical problems for our customers. We are focused on leveraging the latest technologies in Large Language Models (LLMs) and AI Agent systems, while ensuring that the solutions we develop are cost-effective, secure, and reliable.</p>\n<p>As an AI Agent Engineer, you&#39;ll be at the forefront of deploying AI agents that address real-world challenges. In this role, you will work closely with customers as well as our software and machine learning engineers, ensuring high-impact AI Agent deployments and contributing to the continuous improvement of our core AI platform. You’ll develop intelligent AI agents, integrate them seamlessly with external systems and offer hands-on technical expertise to ensure successful deployments.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Develop, configure, deploy, and optimise AI agents using Cresta’s AI platform and tools.</li>\n<li>Build AI agent integrations with external systems (APIs, databases, CRMs, etc.) to ensure seamless workflow integration.</li>\n<li>Optimise AI agent performance (e.g. fine-tune prompts and configurations) and troubleshoot issues in complex enterprise environments.</li>\n<li>Collaborate with customers and internal stakeholders to gather technical requirements and translate business needs into AI Agent solutions.</li>\n<li>Conduct interactive demos and present compelling proof-of-concepts to prospective customers, proactively gather feedback, and iteratively refine solutions to meet objectives.</li>\n<li>Define project milestones, create implementation plans, and coordinate execution with internal teams to ensure on-time delivery. Provide a tight feedback loop to our product and engineering teams , identifying gaps, building custom tooling, and influencing the roadmap through real-world deployment learnings.</li>\n<li>Collaborate with PMs to define agent goals, iterate rapidly based on customer feedback, and shape product capabilities that maximise customer ROI.</li>\n<li>Serve as a trusted technical advisor for the customer, guiding best practices for AI agent adoption and usage. Provide technical guidance on AI agent best practices, including architecture design, security considerations, and scalability planning.</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.</li>\n<li>3+ years of experience of full time working experience in software development/ consulting, AI/ML engineering, or system integration, or as FDE.</li>\n<li>Proficiency in Python and Golang, with the ability to write clean, efficient code.</li>\n<li>Familiarity with AI/ML concepts. Hands-on experience with large language models (LLMs), and prompt engineering techniques are strongly preferred.</li>\n<li>Strong understanding of general AI agent frameworks, function calling, and retrieval-augmented generation (RAG). 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This team operates within the Eastern Standard time zone for collaboration.</p>\n<p>Core working hours are CET 3pm-6pm / EST 9am-12pm.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_55f868ee-839","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Spotify","sameAs":"https://www.spotify.com","logo":"https://logos.yubhub.co/spotify.com.png"},"x-apply-url":"https://jobs.lever.co/spotify/33114d31-b3d0-4bbb-bf7c-ab32596e8969","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$203,795 - $291,136 plus equity","x-skills-required":["Python","PyTorch","NumPy","generative modeling","machine learning","music information retrieval","speech processing","audio processing","signal processing","probabilistic modeling","computer vision"],"x-skills-preferred":[],"datePosted":"2026-03-31T18:13:35.727Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"North America"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, PyTorch, NumPy, generative modeling, machine learning, music information retrieval, speech processing, audio processing, signal processing, probabilistic modeling, computer vision","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":203795,"maxValue":291136,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_91b6c7f1-54a"},"title":"Product Manager, Gemini App for Devices","description":"<p><strong>About Us</strong></p>\n<p>Artificial Intelligence could be one of humanity&#39;s most useful inventions. 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In this role, you will work closely with our data and infrastructure teams to build, maintain and scale our search platform while ensuring a high-level of performance and reliability.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Building, maintaining and enhancing a fast, reliable and scalable indexing and searching capabilities (web and knowledge)</li>\n<li>Working with search-oriented databases to optimise and fine-tune full search pipelines from document ingestion to retrieval</li>\n<li>Owning our information retrieval systems serving both our internal needs as well as our enterprise customers</li>\n<li>Ensuring that our search capabilities meet the increasing demands of our customers</li>\n<li>Collaborate with internal and external stakeholders to push the boundaries of search reliability, performance, and scale across a range and cloud-native and on-premise services.</li>\n</ul>\n<p>About you:</p>\n<ul>\n<li>7+ years of relevant professional work experience</li>\n<li>Master’s degree in Computer Science, Information Technology or a related field</li>\n<li>Experience building and scaling distributed search engine systems</li>\n<li>Excellent proficiency in backend software development (Python, Go, C++, Rust...)</li>\n<li>Solid proficiency in infrastructure management (Docker, CI/CD, Helm, K8s, Terraform...)</li>\n<li>Good knowledge of cloud-native ecosystems</li>\n<li>Autonomous and self-starter</li>\n<li>Ability to communicate with influence</li>\n</ul>\n<p>Now, it would be ideal if you had experience with:</p>\n<ul>\n<li>AI/ML engineering</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_787f8082-bf4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mistral AI","sameAs":"https://mistral.ai/careers"},"x-apply-url":"https://jobs.lever.co/mistral/70d5293a-9183-40d9-874a-cc08a14d5de6","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["backend software development","infrastructure management","cloud-native ecosystems","search engine systems","information retrieval systems"],"x-skills-preferred":["AI/ML engineering"],"datePosted":"2026-03-10T11:33:01.327Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"backend software development, infrastructure management, cloud-native ecosystems, search engine systems, information retrieval systems, AI/ML engineering"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c952dc65-160"},"title":"AI Machine Learning Engineer: AI Shopping Agents","description":"<p><strong>About Us</strong></p>\n<p>Constructor is a U.S. based company that has been in the market since 2019, building a next-generation platform for search and discovery in ecommerce. Its search engine is entirely invented in-house, utilizing transformers and generative LLMs, and powers over 1 billion queries every day across 150 languages and roughly 100 countries.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Architect and build real-time agentic workflows to handle complex, multi-step user tasks and open-ended queries, providing users with accurate and contextually relevant answers and product suggestions</li>\n<li>Own the end-to-end data lifecycle for AI workflows, including vector database ingestion and indexing</li>\n<li>Design metrics to evaluate the relevance and performance of query results, ensuring alignment with business goals and user expectations</li>\n<li>Generate and rapidly prototype novel product hypotheses that leverage LLMs, RAG, and agentic systems</li>\n<li>Collaborate closely with Product, Design, Analytics, and other engineering teams to translate AI capabilities into tangible, high-quality product features</li>\n<li>Improve the speed, quality, and efficiency of our AI systems and engineering processes</li>\n<li>Take ownership of systems and designs from conception through to deployment and maintenance</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>4+ years of industry experience in related fields, including search, information retrieval, recommendation systems, applied machine learning, and NLP</li>\n<li>Excellent skills in delivering and communicating business value</li>\n<li>Proficient in Python, SQL, and the big data stack for end-to-end ML product development, with experience across the entire pipeline in typical recommendation systems or LLM-based solutions</li>\n<li>Strong grasp of Information Retrieval (IR) techniques (e.g., dense retrieval, re-ranking, chunking strategies)</li>\n<li>Direct experience with Retrieval-Augmented Generation (RAG); experience building autonomous agents is a strong plus</li>\n<li>Nice to have: experience with automatic prompt optimization techniques (e.g., DSPy)</li>\n<li>Solid understanding of ML evaluation methodologies and key IR metrics</li>\n<li>Passion for shipping high-quality products and a self-motivated drive to take ownership of tasks</li>\n</ul>\n<p><strong>Tech Stack</strong></p>\n<ul>\n<li>Core: Python, FastAPI, asyncio, Airflow, Luigi, PySpark, Docker, LangGraph</li>\n<li>Data Stores: Vector Databases, DynamoDB, AWS S3, AWS RDS</li>\n<li>Cloud &amp; MLOps: AWS, Databricks, Ray</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year</li>\n<li>Fully remote team - choose where you live</li>\n<li>Work from home stipend! We want you to have the resources you need to set up your home office</li>\n<li>Apple laptops provided for new employees</li>\n<li>Training and development budget for every employee, refreshed each year</li>\n<li>Maternity &amp; Paternity leave for qualified employees</li>\n<li>Work with smart people who will help you grow and make a meaningful impact</li>\n<li>This position has a base salary range between $80k and $120k USD.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_c952dc65-160","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Constructor","sameAs":"https://apply.workable.com","logo":"https://logos.yubhub.co/j.com.png"},"x-apply-url":"https://apply.workable.com/j/D15079EEBA","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$80k - $120k USD","x-skills-required":["Python","SQL","big data stack","Information Retrieval (IR) techniques","Retrieval-Augmented Generation (RAG)","automatic prompt optimization techniques"],"x-skills-preferred":["DSPy"],"datePosted":"2026-03-09T10:57:19.254Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Oregon"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, SQL, big data stack, Information Retrieval (IR) techniques, Retrieval-Augmented Generation (RAG), automatic prompt optimization techniques, DSPy","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":80000,"maxValue":120000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4bd6468f-bc0"},"title":"Senior Applied Scientist","description":"<p>We&#39;re building the next-generation Grounding Service that powers the latest AI applications—chat assistants, copilots, and autonomous agents—with factual, cited, and trustworthy responses. Our platform stitches together retrieval, reasoning, and real-time data so that large language models stay anchored to enterprise knowledge, the public web, and proprietary tools.</p>\n<p>We&#39;re looking for a Senior Applied Scientist to lead end-to-end science for grounding: inventing retrieval and attribution methods, defining factuality/faithfulness metrics, and shipping production models and APIs that scale to billions of queries. You&#39;ll partner closely with engineering, product, research, and customers to deliver fast, reliable, and explainable answers with source citations across a diverse set of domains and modalities.</p>\n<p>As a team, we value curiosity, pragmatic rigor, and inclusive collaboration. We believe great systems emerge when scientists and engineers co-design metrics, models, and infrastructure—and when we obsess over customer impact, privacy, and safety.</p>\n<p>Responsibilities\n Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact.\n Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images.\n Builds citation and provenance systems (e.g., passage highlighting, quote-level alignment, confidence scoring) to reduce hallucinations and increase user trust.\n Leads experimentation and evaluation using A/B testing, interleaving, NDCG, MRR, precision/recall, and calibration curves to guide measurable trade-offs.\n Advances tool-augmented grounding through schema-aware retrieval, function calling, knowledge graph joins, and real-time connectors to databases, cloud object stores, search indexes, and the web.\n Partners with platform engineering to productionize models with scalable inference, embedding services, feature stores, caching, and privacy-compliant multi-tenant systems.\n Nurtures collaborative relationships with product and business leaders across Microsoft, influencing strategic decisions and driving business impact through technology.\n Authors white papers, contributes to internal tools and services, and may publish research to generate intellectual property.\n Bridges the gap between researchers (e.g., Microsoft Research) and development teams, applying long-term research to solve immediate product needs.\n Leads high-stakes negotiations to ensure cutting-edge technologies are applied practically and effectively.\n Identifies and solves significant business problems using novel, scalable, and data-driven solutions.\n Shapes the direction of Microsoft and the broader industry through pioneering product and tooling work.\n Mentors applied scientists and data scientists, establishing best practices in experimentation, error analysis, and incident review.\n Collaborates cross-functionally with PMs, research, infrastructure, and security teams to align on milestones, SLAs, and safety protocols.\n Communicates clearly through design documentation, progress updates, and presentations to executives and customers.\n Contributes to ethics and privacy policies, identifies bias in product development, and proposes mitigation strategies.</p>\n<p>Qualifications\n Required Qualifications:\n  Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)\n  OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)\n  OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)\n  OR equivalent experience.\n  Minimum of 4 years of hands-on experience designing and building search, retrieval, or ranking systems.\n  Proven track record of shipping LLM-powered or Retrieval-Augmented Generation (RAG) systems into production environments.\n  Solid coding skills and solid foundation in machine learning, with the ability to implement and optimize models effectively.\n  Demonstrated ability to lead through ambiguity, make principled trade-offs, and deliver measurable impact in cross-functional, fast-paced settings.\n Preferred Qualifications:\n  Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)\n  OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)\n  OR equivalent experience.\n  Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL.\n  Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL).\n  Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_4bd6468f-bc0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-38/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Search","Retrieval","Ranking","Machine Learning","Information Retrieval","Large Language Models","Pretraining","Supervised Fine-Tuning","Reinforcement Learning"],"x-skills-preferred":["Information Retrieval","Large Language Models","Pretraining","Supervised Fine-Tuning","Reinforcement Learning"],"datePosted":"2026-03-08T22:18:58.169Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Suzhou"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Search, Retrieval, Ranking, Machine Learning, Information Retrieval, Large Language Models, Pretraining, Supervised Fine-Tuning, Reinforcement Learning, Information Retrieval, Large Language Models, Pretraining, Supervised Fine-Tuning, Reinforcement Learning"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d0214534-b6a"},"title":"Senior Applied Scientist","description":"<p>We&#39;re building the next-generation Grounding Service that powers the latest AI applications—chat assistants, copilots, and autonomous agents—with factual, cited, and trustworthy responses. Our platform stitches together retrieval, reasoning, and real-time data so that large language models stay anchored to enterprise knowledge, the public web, and proprietary tools. We&#39;re looking for a Senior Applied Scientist to lead end-to-end science for grounding: inventing retrieval and attribution methods, defining factuality/faithfulness metrics, and shipping production models and APIs that scale to billions of queries. You&#39;ll partner closely with engineering, product, research, and customers to deliver fast, reliable, and explainable answers with source citations across a diverse set of domains and modalities. As a team, we value curiosity, pragmatic rigor, and inclusive collaboration. We believe great systems emerge when scientists and engineers co-design metrics, models, and infrastructure—and when we obsess over customer impact, privacy, and safety. Microsoft&#39;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction. Responsibilities</p>\n<p>Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact. Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images. Builds citation and provenance systems (e.g., passage highlighting, quote-level alignment, confidence scoring) to reduce hallucinations and increase user trust. Leads experimentation and evaluation using A/B testing, interleaving, NDCG, MRR, precision/recall, and calibration curves to guide measurable trade-offs. Advances tool-augmented grounding through schema-aware retrieval, function calling, knowledge graph joins, and real-time connectors to databases, cloud object stores, search indexes, and the web. Partners with platform engineering to productionize models with scalable inference, embedding services, feature stores, caching, and privacy-compliant multi-tenant systems. Nurtures collaborative relationships with product and business leaders across Microsoft, influencing strategic decisions and driving business impact through technology. Authors white papers, contributes to internal tools and services, and may publish research to generate intellectual property. Bridges the gap between researchers (e.g., Microsoft Research) and development teams, applying long-term research to solve immediate product needs. Leads high-stakes negotiations to ensure cutting-edge technologies are applied practically and effectively. Identifies and solves significant business problems using novel, scalable, and data-driven solutions. Shapes the direction of Microsoft and the broader industry through pioneering product and tooling work. Mentors applied scientists and data scientists, establishing best practices in experimentation, error analysis, and incident review. Collaborates cross-functionally with PMs, research, infrastructure, and security teams to align on milestones, SLAs, and safety protocols. Communicates clearly through design documentation, progress updates, and presentations to executives and customers. Contributes to ethics and privacy policies, identifies bias in product development, and proposes mitigation strategies.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d0214534-b6a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-37/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Machine Learning","Information Retrieval","Large Language Model Development","Pretraining","Supervised Fine-Tuning","Reinforcement Learning","Optimizing LLM Inference"],"x-skills-preferred":["Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field","6+ years related experience (e.g., statistics, predictive analytics, research)","Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL","Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL)","Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects"],"datePosted":"2026-03-08T22:16:41.766Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Beijing"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Machine Learning, Information Retrieval, Large Language Model Development, Pretraining, Supervised Fine-Tuning, Reinforcement Learning, Optimizing LLM Inference, Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field, 6+ years related experience (e.g., statistics, predictive analytics, research), Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL, Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL), Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_714d4a02-1c4"},"title":"Applied Scientist","description":"<p>Imagine shaping the future of local search for millions of users worldwide. At Bing Places, you&#39;ll join a team that powers business entity relevance on the search results page. You&#39;ll work on cutting-edge tools and metrics that ensure users find the most accurate and meaningful local results. Our team thrives on innovation, leveraging large and small language models, and advanced measurement systems to deliver exceptional quality.</p>\n<p>As a Applied Scientist in Bing Places, you will design new relevance metrics, build labeling pipelines, and fine-tune language models to improve search quality. You&#39;ll work on prompt engineering, implement modern language models techniques like Retrieval Augmented Generation, and create scalable workflows for measurement and evaluation.</p>\n<p>This opportunity will allow you to:</p>\n<ul>\n<li>Accelerate your career growth by working on state-of-the-art AI systems.</li>\n<li>Develop deep expertise in prompt engineering and model tuning.</li>\n<li>Hone your skills in building robust data pipelines and quality frameworks.</li>\n</ul>\n<p>Microsoft&#39;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and implement new relevance metrics to measure and improve local search quality.</li>\n<li>Develop and optimize LLM/SLM labeling pipelines for high-throughput, consistent quality judgments.</li>\n<li>Engineer and fine-tune prompts for LLMs to enhance query understanding and classification accuracy.</li>\n<li>Apply modern LLM techniques such as retrieval-augmented generation for improved grounding and relevance.</li>\n<li>Build scalable workflows and dashboards for measurement, evaluation cycles, and quality checks.</li>\n<li>Analyze failure modes and improve prompt rubrics to reduce defect rates and enhance labeling consistency.</li>\n<li>Collaborate with cross-functional teams to integrate metrics and labeling systems into production environments.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND hands on experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND hands on experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.</li>\n</ul>\n<p>Other Requirements:</p>\n<ul>\n<li>Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_714d4a02-1c4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/applied-scientist-7/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","LLM/SLM labeling pipelines","Prompt engineering","Model tuning","Data pipelines","Quality frameworks"],"x-skills-preferred":["Retrieval Augmented Generation","Scalable workflows","Dashboards","Measurement","Evaluation cycles","Quality checks"],"datePosted":"2026-03-08T22:15:35.607Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Barcelona"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, LLM/SLM labeling pipelines, Prompt engineering, Model tuning, Data pipelines, Quality frameworks, Retrieval Augmented Generation, Scalable workflows, Dashboards, Measurement, Evaluation cycles, Quality checks"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_98d7335f-4d4"},"title":"Applied AI Engineer","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>Working closely with our Sales, Product, and Engineering teams, you&#39;ll guide customers from technical discovery through successful deployment. You&#39;ll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.</strong></p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Serve as a technical advisor to Anthropic customers as they deploy new products &amp; workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success</li>\n</ul>\n<ul>\n<li>Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation</li>\n</ul>\n<ul>\n<li>Guide technical architecture decisions and help customers build state-of-the-art products &amp; workflows with LLMs via API</li>\n</ul>\n<ul>\n<li>Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API</li>\n</ul>\n<ul>\n<li>Lead hands-on technical workshops and code reviews with customer engineering teams</li>\n</ul>\n<ul>\n<li>Identify common design patterns and contribute insights back to our Product and Engineering teams</li>\n</ul>\n<ul>\n<li>Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks</li>\n</ul>\n<ul>\n<li>Travel occasionally to customer sites for workshops, implementation support, and building relationships</li>\n</ul>\n<ul>\n<li>Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space</li>\n</ul>\n<p><strong>You may be a good fit if you have:</strong></p>\n<ul>\n<li>4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers</li>\n</ul>\n<ul>\n<li>Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale</li>\n</ul>\n<ul>\n<li>Strong programming skills with proficiency in Python and experience building production applications</li>\n</ul>\n<ul>\n<li>Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.</li>\n</ul>\n<ul>\n<li>Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems</li>\n</ul>\n<ul>\n<li>High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity</li>\n</ul>\n<ul>\n<li>Passion for advancing safe, beneficial AI systems through creative technical applications</li>\n</ul>\n<ul>\n<li>Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach</li>\n</ul>\n<p><strong>Deadline to apply: None. Applications will be reviewed on a rolling basis.</strong></p>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</strong></p>\n<p><strong>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</strong></p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.</strong></p>\n<p><strong>Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_98d7335f-4d4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5055488008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Production experience with LLMs","Advanced prompt engineering","Agent development","Evaluation frameworks","Deployment at scale","Strong programming skills with proficiency in Python","Experience building production applications","Expertise working with common LLM implementation patterns","Prompt engineering","Evaluation frameworks","Agent frameworks","Retrieval frameworks"],"x-skills-preferred":["Intellectual openness","High cooperation mindset","Passion for advancing safe, beneficial AI systems","Exceptional communication skills"],"datePosted":"2026-03-08T13:59:34.314Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Tokyo, Japan"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Production experience with LLMs, Advanced prompt engineering, Agent development, Evaluation frameworks, Deployment at scale, Strong programming skills with proficiency in Python, Experience building production applications, Expertise working with common LLM implementation patterns, Prompt engineering, Evaluation frameworks, Agent frameworks, Retrieval frameworks, Intellectual openness, High cooperation mindset, Passion for advancing safe, beneficial AI systems, Exceptional communication skills"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_74e83779-8ca"},"title":"Applied AI Engineer","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p>\n<p><strong>Working closely with our Sales, Product, and Engineering teams, you&#39;ll guide customers from technical discovery through successful deployment. You&#39;ll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability.</strong></p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Serve as a technical advisor to Anthropic customers as they deploy new products &amp; workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success</li>\n<li>Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation</li>\n<li>Guide technical architecture decisions and help customers build state-of-the-art products &amp; workflows with LLMs via API</li>\n<li>Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API</li>\n<li>Lead hands-on technical workshops and code reviews with customer engineering teams</li>\n<li>Identify common design patterns and contribute insights back to our Product and Engineering teams</li>\n<li>Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks</li>\n<li>Travel occasionally to customer sites for workshops, implementation support, and building relationships</li>\n<li>Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space</li>\n</ul>\n<p><strong>You may be a good fit if you have:</strong></p>\n<ul>\n<li>4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers</li>\n<li>Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale</li>\n<li>Strong programming skills with proficiency in Python and experience building production applications</li>\n<li>Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.</li>\n<li>Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems</li>\n<li>High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity</li>\n<li>Passion for advancing safe, beneficial AI systems through creative technical applications</li>\n<li>Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach</li>\n<li>Fluent in both Korean and English</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.</p>\n<p>Visa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.</p>\n<p>We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.</p>\n<p>Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</p>\n<p><strong>How we&#39;re different</strong></p>\n<p>We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We&#39;re an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.</p>\n<p>The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_74e83779-8ca","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5014500008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Production experience with LLMs","Advanced prompt engineering","Agent development","Evaluation frameworks","Deployment at scale","Strong programming skills with proficiency in Python","Experience building production applications","Expertise working with common LLM implementation patterns","Prompt engineering","Evaluation frameworks","Agent frameworks","Retrieval frameworks"],"x-skills-preferred":["Intellectual openness","High cooperation mindset","Passion for advancing safe, beneficial AI systems","Exceptional communication skills","Fluent in both Korean and English"],"datePosted":"2026-03-08T13:57:43.523Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seoul, South Korea"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Production experience with LLMs, Advanced prompt engineering, Agent development, Evaluation frameworks, Deployment at scale, Strong programming skills with proficiency in Python, Experience building production applications, Expertise working with common LLM implementation patterns, Prompt engineering, Evaluation frameworks, Agent frameworks, Retrieval frameworks, Intellectual openness, High cooperation mindset, Passion for advancing safe, beneficial AI systems, Exceptional communication skills, Fluent in both Korean and English"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_50d6a6cf-6c0"},"title":"AI Success Engineer","description":"<p><strong>AI Success Engineer - São Paulo, Brazil</strong></p>\n<p><strong>Location</strong></p>\n<p>São Paulo</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p><strong>About the Team</strong></p>\n<p>OpenAI’s AI Success Engineer team partners with the world’s most ambitious organisations to translate cutting-edge AI into real business value. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery.</p>\n<p>Our customers range from fast-growing digital natives to the largest global enterprises, government agencies, and educational institutions. Every engagement is an opportunity to shape how AI changes work, productivity, and innovation. This role sits at the centre of that mission.</p>\n<p><strong>About the Role</strong></p>\n<p>The AI Success Engineer role is the primary post-sales point of contact for OpenAI’s most important customers. You are responsible for driving account health and adoption, ensuring technical readiness, identifying new use cases, and delivering measurable value to our customers with OpenAI’s ambitiously growing platform.</p>\n<p>This role blends technical depth, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration, oversee deployment plans, and guide customers toward high-impact use cases that showcase the full value of our platform.</p>\n<p>You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible business impact.</p>\n<p>This role is based in São Paulo (office 3x a week) and we provide relocation support to new employees.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realisation.</li>\n</ul>\n<ul>\n<li>Own account health, adoption velocity, and ongoing technical deployment and success across your portfolio.</li>\n</ul>\n<ul>\n<li>Be an expert in all of OpenAI products across our API and agentic platform, Codex, ChatGPT Enterprise, and more and conduct technical enablement and configuration sessions across them.</li>\n</ul>\n<ul>\n<li>Identify and validate use cases by embedding with customer teams to understand workflows and pain points.</li>\n</ul>\n<ul>\n<li>Lead account-level coordination across multiple work streams, including new product activation, change management, and customer rollout and deployment planning.</li>\n</ul>\n<ul>\n<li>Build strong relationships with executive sponsors and technical stakeholders and help align business goals with OpenAI capabilities.</li>\n</ul>\n<ul>\n<li>Translate customer objectives into an actionable adoption roadmap with clear sequencing, milestones, and KPIs.</li>\n</ul>\n<ul>\n<li>Partner with Solutions Architecture, Product, Engineering and Research by surfacing customer feedback, field patterns, and technical blockers and act as a cross-functional navigator who keeps teams aligned, informed, and moving toward customer outcomes.</li>\n</ul>\n<ul>\n<li>Guide value realisation and measure impact through baselines, KPI definition, and post-deployment reporting.</li>\n</ul>\n<ul>\n<li>Facilitate workshops on use case design, adoption best practices, champion building, and internal enablement.</li>\n</ul>\n<ul>\n<li>Help drive expansions by identifying high-leverage opportunities where OpenAI’s platform can power new workflows or lines of business.</li>\n</ul>\n<ul>\n<li>Serve as the technical advisor for existing customer implementations by guiding and optimising account setup, configuration, etc.</li>\n</ul>\n<p><strong>You’ll thrive in this role if you:</strong></p>\n<ul>\n<li>8+ years of experience in technical customer-facing roles such as technical account management, technical GenAI consulting or deployment roles, solutions architecture, technical delivery leadership, customer architecture or engineering, or other deep technical enterprise adoption work.</li>\n</ul>\n<ul>\n<li>Deep, hands-on knowledge of OpenAI product capabilities, APIs, SDKs, connectors, and common integration patterns and able to explain model behaviour, limitations, technical trade-offs, embeddings, retrieval augmentation, and approaches to fine-tuning or custom model usage.</li>\n</ul>\n<ul>\n<li>Understanding and familiarity with coding languages like Python or JavaScript, and comfort with REST APIs, SDKs, automation, CI/CD, containers, and cloud platforms.</li>\n</ul>\n<ul>\n<li>Can translate technical concepts into clear business language and help customers understand the strategic impact of AI technologies.</li>\n</ul>\n<ul>\n<li>Can show a strong record of driving technical deployments with hands-on on customer work and owning impactful adoption and value for large enterprise customers with complex environments and multiple stakeholders.</li>\n</ul>\n<ul>\n<li>Are comfortable embedding with customers to map workflows, identify requirements, and diagnose adoption challenges.</li>\n</ul>\n<ul>\n<li>Have excellent project and program management instincts and can lead multi-work stream initiatives with clarity and structure.</li>\n</ul>\n<ul>\n<li>Enjoy being a thought partner for C-level stakeholders while also diving deep with technical teams.</li>\n</ul>\n<ul>\n<li>Operate with high ownership and can manage fast decision-making, context switching, and dynamic customer needs.</li>\n</ul>\n<ul>\n<li>Have a strong record of driving technical deployments with hands-on on customer work and owning impactful adoption and value for large enterprise customers with complex environments and multiple stakeholders.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of human endeavour.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_50d6a6cf-6c0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/c7d41e7c-7e84-4af5-85b9-bbc1a3b08e87","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Deep, hands-on knowledge of OpenAI product capabilities, APIs, SDKs, connectors, and common integration patterns","Understanding and familiarity with coding languages like Python or JavaScript","Comfort with REST APIs, SDKs, automation, CI/CD, containers, and cloud platforms","Ability to explain model behaviour, limitations, technical trade-offs, embeddings, retrieval augmentation, and approaches to fine-tuning or custom model usage","Strong record of driving technical deployments with hands-on on customer work and owning impactful adoption and value for large enterprise customers with complex environments and multiple stakeholders"],"x-skills-preferred":["Technical account management","Technical GenAI consulting or deployment roles","Solutions architecture","Technical delivery leadership","Customer architecture or engineering"],"datePosted":"2026-03-06T18:38:42.587Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"São Paulo"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Deep, hands-on knowledge of OpenAI product capabilities, APIs, SDKs, connectors, and common integration patterns, Understanding and familiarity with coding languages like Python or JavaScript, Comfort with REST APIs, SDKs, automation, CI/CD, containers, and cloud platforms, Ability to explain model behaviour, limitations, technical trade-offs, embeddings, retrieval augmentation, and approaches to fine-tuning or custom model usage, Strong record of driving technical deployments with hands-on on customer work and owning impactful adoption and value for large enterprise customers with complex environments and multiple stakeholders, Technical account management, Technical GenAI consulting or deployment roles, Solutions architecture, Technical delivery leadership, Customer architecture or engineering"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_75ad55ca-61b"},"title":"Research Engineer / Research Scientist - Foundations Retrieval IC","description":"<p><strong>Job Posting</strong></p>\n<p><strong>Research Engineer / Research Scientist - Foundations Retrieval IC</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Research</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$445K – $555K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science.</p>\n<p><strong>About the Role</strong></p>\n<p>We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods.</p>\n<p>This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact.</p>\n<p>This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning.</li>\n</ul>\n<ul>\n<li>Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluating, and integrating embeddings into frontier models.</li>\n</ul>\n<ul>\n<li>Drive innovation in dense, sparse, and hybrid representation techniques, metric learning, and learning-to-retrieve systems.</li>\n</ul>\n<ul>\n<li>Collaborate closely with Pretraining, Inference, and other Research teams to integrate retrieval throughout the model lifecycle</li>\n</ul>\n<ul>\n<li>Contribute to OpenAI’s long-term vision of AI systems with memory and knowledge access capabilities rooted in learned representations.</li>\n</ul>\n<p><strong>You Might Thrive in This Role If You Have</strong></p>\n<ul>\n<li>Proven experience leading high-performance teams of researchers or engineers in ML infrastructure or foundational research.</li>\n</ul>\n<ul>\n<li>Deep technical expertise in representation learning, embedding models, or vector retrieval systems.</li>\n</ul>\n<ul>\n<li>Familiarity with transformer-based LLMs and how embedding spaces can interact with language model objectives.</li>\n</ul>\n<ul>\n<li>Research experience in areas such as contrastive learning, supervised or unsupervised embedding learning, or metric learning.</li>\n</ul>\n<ul>\n<li>A track record of building or scaling large machine learning systems, particularly embedding pipelines in production or research contexts.</li>\n</ul>\n<ul>\n<li>A first-principles mindset for challenging assumptions about how retrieval and memory should work for large models.</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_75ad55ca-61b","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/020b2aae-8be0-408c-ab49-20eefa8541af","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$445K – $555K • Offers Equity","x-skills-required":["representation learning","embedding models","vector retrieval systems","transformer-based LLMs","contrastive learning","supervised or unsupervised embedding learning","metric learning"],"x-skills-preferred":["ML infrastructure","foundational research","large machine learning systems","embedding pipelines"],"datePosted":"2026-03-06T18:35:38.299Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"representation learning, embedding models, vector retrieval systems, transformer-based LLMs, contrastive learning, supervised or unsupervised embedding learning, metric learning, ML infrastructure, foundational research, large machine learning systems, embedding pipelines","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":445000,"maxValue":555000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e653d92c-645"},"title":"AI Success Engineer","description":"<p><strong>AI Success Engineer</strong></p>\n<p><strong>About the Team</strong></p>\n<p>OpenAI’s AI Success Engineer team partners with the world’s most ambitious organisations to translate cutting-edge AI into real business value. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery.</p>\n<p><strong>About the Role</strong></p>\n<p>The Success Engineer role is the primary post-sales point of contact for a set of OpenAI’s most important customers. You are responsible for driving account health and adoption, ensuring technical readiness, identifying new use cases, and delivering measurable value to our customers with OpenAI’s platform.</p>\n<p>This role blends technical leadership, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration and enablement, oversee deployment plans, and guide customers toward high-impact use cases that showcase the full value of our platform.</p>\n<p>You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible business impact.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realization</li>\n</ul>\n<ul>\n<li>Own account health, adoption velocity, and ongoing technical deployment and success across your portfolio</li>\n</ul>\n<ul>\n<li>Conduct technical enablement and configuration sessions across our broad product portfolio</li>\n</ul>\n<ul>\n<li>Identify and validate use cases by embedding with customer teams to understand workflows and pain points</li>\n</ul>\n<ul>\n<li>Lead account level coordination across multiple workstreams, including new product activation, change management, and customer rollout and deployment planning</li>\n</ul>\n<ul>\n<li>Build strong relationships with executive sponsors and technical stakeholders and help align business goals with OpenAI capabilities</li>\n</ul>\n<ul>\n<li>Translate customer objectives into an actionable adoption roadmap with clear sequencing, milestones, and KPIs</li>\n</ul>\n<ul>\n<li>Partner with Solutions Architecture, Product, Engineering and Research by surfacing customer feedback, field patterns, and technical blockers and act as a cross-functional navigator who keeps teams aligned, informed, and moving toward customer outcomes</li>\n</ul>\n<ul>\n<li>Guide value realization and measure impact through baselines, KPI definition, and post-deployment reporting</li>\n</ul>\n<ul>\n<li>Facilitate workshops on use case design, adoption best practices, champion building, and internal enablement</li>\n</ul>\n<ul>\n<li>Help drive expansions by identifying high-leverage opportunities where OpenAI’s platform can power new workflows or lines of business</li>\n</ul>\n<ul>\n<li>Serve as the technical advisor for existing customer implementations by guiding and optimizing account setup, configuration, etc.</li>\n</ul>\n<p><strong>You’ll thrive in this role if you:</strong></p>\n<ul>\n<li>8+ years of experience in technical customer-facing roles such as technical account management, technical GenAI consulting or deployment roles, solutions architecture, technical delivery leadership, or deep technical enterprise adoption work</li>\n</ul>\n<ul>\n<li>Deep, hands-on knowledge of OpenAI product capabilities, APIs, SDKs, connectors, and common integration patterns and able to explain model behavior, limitations, technical tradeoffs, embeddings, retrieval augmentation, and approaches to fine-tuning or custom model usage</li>\n</ul>\n<ul>\n<li>Can translate technical concepts into clear business language and help customers understand the strategic impact of AI technologies</li>\n</ul>\n<ul>\n<li>Are comfortable embedding with customers to map workflows, identify requirements, and diagnose adoption challenges</li>\n</ul>\n<ul>\n<li>Have excellent project and program management instincts and can lead multi-workstream initiatives with clarity and structure</li>\n</ul>\n<ul>\n<li>Enjoy being a thought partner for C-level stakeholders while also diving deep with technical teams</li>\n</ul>\n<ul>\n<li>Operate with high ownership and can manage fast decision making, context switching, and dynamic customer needs</li>\n</ul>\n<ul>\n<li>Have a strong record of driving technical deployments with hands-on on customer work and owning impactful adoption and value for large enterprise customers with complex environments and multiple stakeholders</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. 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If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p>More details about our benefits are available to candidates during the hiring process.</p>\n<p>This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.</p>\n<p><strong>About the Team</strong></p>\n<p>We bring OpenAI&#39;s technology to the world through products like ChatGPT and the OpenAI API.</p>\n<p>We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.</p>\n<p><strong>About the Role</strong></p>\n<p>We are looking for an experienced Research Engineer to work on retrieval &amp; search problems across our API and ChatGPT. As the AI landscape has evolved over the last few years, retrieval &amp; search have emerged as key use cases for our models, and we are investing in ensuring that we can offer these search-based product experiences for our users. 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We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products.</p>\n<p><strong>About the Role</strong></p>\n<p>A systems research internship is for people who love the real-world intersection of systems-engineering and research: you’ll investigate a hard systems problem, build something meaningful, and measure it carefully. The goal is practical impact—making Applied Systems better: more efficient, more scalable, and more reliable.</p>\n<p>OpenAI is currently recruiting for candidates interested in a 13-week, paid, in-person internship based in our San Francisco office during Summer 2026. In some cases, it may be extended for an additional 13 weeks (for a total of up to 26 weeks), based on team needs, candidate interest, and performance.</p>\n<p><strong>In this role, you will typically focus on improving real systems in areas like:</strong></p>\n<ul>\n<li>Distributed systems &amp; storage (throughput, latency, consistency, durability)</li>\n</ul>\n<ul>\n<li>Compute &amp; scheduling (GPU/accelerator utilization, job orchestration, queuing)</li>\n</ul>\n<ul>\n<li>Performance engineering (profiling, bottlenecks, scalability, capacity planning)</li>\n</ul>\n<ul>\n<li>Reliability &amp; observability (fault tolerance, monitoring, incident learning)</li>\n</ul>\n<ul>\n<li>Networking &amp; data pipelines (data movement, caching, streaming efficiency)</li>\n</ul>\n<ul>\n<li>Systems for ML (training/inference performance, evaluation infrastructure, tooling)</li>\n</ul>\n<p>Most projects involve some of these steps:</p>\n<ul>\n<li>Defining a clear hypothesis (“we think X will reduce latency by Y under Z”)</li>\n</ul>\n<ul>\n<li>Instrumenting existing production systems, gathering metrics and detailed analysis to validate the hypothesis</li>\n</ul>\n<ul>\n<li>Building or modifying a real system (prototype or production-quality improvements when appropriate)</li>\n</ul>\n<ul>\n<li>Running experiments/benchmarks and analyzing results</li>\n</ul>\n<ul>\n<li>Communicating tradeoffs and recommendations clearly</li>\n</ul>\n<ul>\n<li>Publishing the research work in technical journals and conferences</li>\n</ul>\n<p><strong>Your background looks something like:</strong></p>\n<ul>\n<li>Currently pursuing a PhD in Computer Science, Computer Engineering, or relevant technical field</li>\n</ul>\n<ul>\n<li>Proficiency with Coding in c++, Java, python, rust, etc</li>\n</ul>\n<ul>\n<li>Doing ongoing research on systems topics such as DL/ML, information retrieval, systems security and cryptography, databases, networking, distributed systems, and compilers, etc</li>\n</ul>\n<ul>\n<li>Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. 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Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.</p>\n<p>A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.</p>\n<p><strong>You Will</strong></p>\n<p>As a Senior Machine Learning Engineer on the AI Platform team, you will be a key contributor to building the cutting-edge systems that power AI at Roblox. You will focus on one of three high-impact tracks:</p>\n<p><strong>Track 1: AI Platform Projects</strong></p>\n<ul>\n<li>Pioneer next-generation AI tooling to enhance the efficiency, cost, and usability of ML@Roblox.</li>\n<li>Build and maintain core platform components: Serving Layer, Model Registry, Pipeline Orchestrator, and Training/Inference control planes.</li>\n<li>Design great developer experiences (paved-road templates, tooling, visualizations) to reduce time-to-production and ensure foundational AI systems are scalable and reliable.</li>\n</ul>\n<p><strong>Track 2: Distributed Inference &amp; Systems Optimization</strong></p>\n<ul>\n<li>Architect and implement scalable distributed inference systems for efficiently serving LLMs and Large Recommender Models at massive scale.</li>\n<li>Conduct deep, low-level performance analysis and optimize ML models (using techniques like continuous batching, speculative decoding, and quantization) and systems on GPU architectures to maintain peak performance and stability.</li>\n</ul>\n<p><strong>Track 3: Information Retrieval &amp; RAG for Gen AI</strong></p>\n<ul>\n<li>Lead the design and development of Retrieval-Augmented Generation (RAG) systems.</li>\n<li>Build and maintain core information retrieval infrastructure—vector databases and knowledge graphs—to enable accurate grounding of Gen AI models.</li>\n<li>Ship language models and 3D objects as a service for the Roblox community, making creation easier.</li>\n</ul>\n<p><strong>You Have</strong></p>\n<ul>\n<li>Possessing or pursuing a Ph.D. in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field, with a thesis aligned to Roblox’s research areas.</li>\n<li>Experience with high performance distributed systems, ML Infrastructure, LLM fine tuning/RL, Information Retrieval and Gen AI context generation.</li>\n<li>Expertise in one or more of the following key areas:</li>\n<li>AI/ML Platform Data stores - Features stores, Vector DBs and Knowledge Graphs.</li>\n<li>LLMs - Fine tuning, Safety.</li>\n<li>Agentic systems - Agent evaluation, context engineering.</li>\n</ul>\n<ul>\n<li>Experience building agentic applications with context for real world applications.</li>\n<li>Collaborative mindset and experience integrating and deploying optimized models with cross-functional teams, including data scientists and software engineers.</li>\n<li>Experience with graph databases and large-scale GNNs (Graph Neural Networks)</li>\n<li>Experience working with Kubernetes</li>\n<li>Experience working with one or more cloud providers (e.g., AWS, Azure, GCP)</li>\n<li>Experience working with high availability systems</li>\n<li>Experience working with ML models, LLMs or other AI systems</li>\n</ul>\n<p>You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.</p>\n<p>As you apply, you can find more information about our process by signing up for Speak\\_. You&#39;ll gain access to our practice assessment, comprehensive guides, FAQs, and modules designed to help you ace the hiring process.</p>\n<p>For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. 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Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.</p>\n<p>We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.</p>\n<p>A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.</p>\n<p>Recommendation Systems are a key growth lever at Roblox, driving retention, engagement, and monetization for hundreds of millions of users. This role offers the unique opportunity to redefine how users search and discover everything from the most interesting immersive experiences and digital avatars in our Marketplace to personalized advertising. You will solve a diverse range of high-scale ranking, retrieval, and personalization problems across our platform.</p>\n<p>We combine cutting-edge research —including deep learning, generative AI, and reinforcement learning techniques— with large-scale engineering to bridge experimentation and production; you&#39;ll design algorithms that operate at massive scale and shape the next generation of recommender systems for user-generated content.</p>\n<p><strong>Teams Hiring for This Role</strong></p>\n<ul>\n<li><strong>Search:</strong> powers major recommendation surfaces—drives user engagement by redesigning core surfaces and search/homepage ranking</li>\n</ul>\n<ul>\n<li><strong>Notifications:</strong> owns the distributed systems and ML platform that transform billions of Roblox signals into high‑value notifications for hundreds of millions of players.</li>\n</ul>\n<ul>\n<li><strong>Economy:</strong> builds the ML backbone for marketplace, monetization, and commerce (including fraud, pricing, and bundling)</li>\n</ul>\n<ul>\n<li><strong>Ads &amp; Brands:</strong> focuses on ranking, retrieval, and marketplace/auction theory to optimize sponsored content delivery.</li>\n</ul>\n<ul>\n<li><strong>Safety, Alt Defense:</strong> architects a massive-scale detection engine that identifies recidivist bad actors across billions of accounts to ensure the long-term integrity of the Roblox community.</li>\n</ul>\n<p><strong>You Will</strong></p>\n<ul>\n<li>Design and implement large-scale recommendation systems that power discovery across Roblox’s surfaces — experiences, avatars, and creator content.</li>\n</ul>\n<ul>\n<li>Develop deep learning models for ranking, retrieval, and personalization using approaches in multimodal models, LLMs, and generative AI.</li>\n</ul>\n<ul>\n<li>Collaborate with applied researchers, engineers, and product teams to advance experimentation and accelerate innovation.</li>\n</ul>\n<ul>\n<li>Translate research into production systems that impact hundreds of millions of daily active users.</li>\n</ul>\n<ul>\n<li>Work backward from user and product needs to deliver ML solutions that drive engagement, retention, and ecosystem growth.</li>\n</ul>\n<p><strong>You Have</strong></p>\n<ul>\n<li>Possessing or pursuing a PhD in computer science, engineering, or a related field, with a thesis aligned to Roblox’s research areas.</li>\n</ul>\n<ul>\n<li>Expertise in one or more areas: recommender systems, search systems, information retrieval, or generative models (e.g., LLMs, VLMs, VLAs)</li>\n</ul>\n<ul>\n<li>Ability to design and architect systems for efficient personalization and user interest modeling using advanced attention mechanisms (e.g., sparse/linear attention).</li>\n</ul>\n<ul>\n<li>A strong research track record, evidenced by multiple publications and presentations in top-tier, peer-reviewed venues (e.g., SIGIR, KDD, RecSys, ICLR, ICML, NeurIPS)</li>\n</ul>\n<ul>\n<li>Proficiency in one or more programming languages (e.g., Python, C++, Go, Java) and experience building and optimizing large-scale systems.</li>\n</ul>\n<p>You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.</p>\n<p>As you apply, you can find more information about our process by signing up for Speak\\_. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the field of artificial intelligence. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI and research organization.</p>\n<p><strong>About the Role</strong></p>\n<p>We are a team of applied scientists working on machine learning components in the whole sponsored search stack. Our team works on problems related to machine learning, deep learning, natural language processing, multi-arm bandit, optimization, information retrieval, and auction theory, among others. Our work entails building large-scale machine learning systems for ad matching, filtration, ranking, and multi objective optimization, and several other ML-driven business problems.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Conduct in-depth market research across AI and research sectors, identifying emerging trends, competitive threats, and partnership opportunities that directly inform the company&#39;s quarterly strategic planning sessions</li>\n<li>Design, implement, analyze, tune complex algorithms and ML systems and the supporting infrastructure for operating on large datasets</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>MS/BS in CS/EE, mathematical or machine learning related disciplines, with 10 or more years of experience</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Solid understanding of probability, statistics, machine learning, data science</li>\n<li>A/B testing &amp; analysis of ML models, and optimizing models for accuracy</li>\n<li>Experience with Hadoop, Spark, or other distributed computing systems for large-scale training &amp; prediction with ML models</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>End-to-end system design: data analysis, feature engineering, technique selection &amp; implementation, debugging, and maintenance in production</li>\n<li>Experience implementing machine learning algorithms or research papers from scratch</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary and benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n<li>Access to cutting-edge technology and resources</li>\n<li>Flexible work arrangements and work-life balance</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f5e6e615-f4f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-2/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package","x-skills-required":["machine learning","deep learning","natural language processing","multi-arm bandit","optimization","information retrieval","auction theory"],"x-skills-preferred":["TensorFlow","PyTorch","Hadoop","Spark"],"datePosted":"2026-03-06T07:33:46.212Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bengaluru"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, natural language processing, multi-arm bandit, optimization, information retrieval, auction theory, TensorFlow, PyTorch, Hadoop, Spark"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_76d1916c-bb4"},"title":"Applied Scientist II","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Applied Scientist II at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI market.</p>\n<p><strong>About the Role</strong></p>\n<p>Our team focuses on understanding and predicting how the user interacts with the ads on the search results page. The probability that a user will click on an ad is one of the most critical inputs used in ranking the ads. Similarly, the probability of interacting with the advertiser’s page is important for measuring advertiser and user satisfaction. This position as an Applied Scientist II is for the modeling team, which builds machine learned models for predicting such events.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Designing and building efficient models for predicting user interactions with ads and advertiser’s pages.</li>\n<li>Designing and overseeing large-scale, long-term experiments to improve the health of the marketplace using advanced statistics and machine learning.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research).</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization and Bayesian inference.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Excellent problem solving and data analysis skills, effective communication skills, both verbal and written.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_76d1916c-bb4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/applied-scientist-ii-5/","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"USD $100,600 – $199,000 per year","x-skills-required":["statistical machine learning","deep learning","data mining","causal inference","information retrieval","game theory","mechanism design","optimization","Bayesian inference"],"x-skills-preferred":["research experience in statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference"],"datePosted":"2026-03-06T07:32:51.127Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization, Bayesian inference, research experience in statistical machine learning, deep learning, data mining, causal inference, information retrieval, and Bayesian inference","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":100600,"maxValue":199000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3fe213ad-1b0"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI-powered quality understanding and recommendation systems.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Applied Scientist, you&#39;ll lead the science behind Discover&#39;s ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Lead content-quality understanding at scale.</li>\n<li>Advance the recommendation &amp; ranking stack.</li>\n<li>Own evaluation and experimentation.</li>\n<li>Champion safety &amp; trust.</li>\n<li>Scale E2E ML systems.</li>\n<li>Mentor &amp; influence.</li>\n<li>Stay close to users.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>6+ years related experience (e.g., statistics, predictive analytics, research).</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Expertise with LLMs (prompting, finetuning, RAG), multimodal modeling, and retrieval-augmented recommendation; familiarity with counterfactual learning and multi-objective optimization.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Demonstrated ability to lead cross-disciplinary efforts (PM, ENG, UXR, editorial/policy) from idea to shipped impact; mentoring scientists and setting technical vision.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_3fe213ad-1b0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-14/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary","x-skills-required":["LLMs","multimodal modeling","retrieval-augmented recommendation","counterfactual learning","multi-objective optimization"],"x-skills-preferred":["PyTorch","Azure ML","Kusto","Synapse","Azure AI Foundry"],"datePosted":"2026-03-06T07:31:53.651Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, multimodal modeling, retrieval-augmented recommendation, counterfactual learning, multi-objective optimization, PyTorch, Azure ML, Kusto, Synapse, Azure AI Foundry"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ebbb8b97-082"},"title":"Member of Technical Staff - Principal Backend Engineer, Copilot Memory and Personalization","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff - Principal Backend Engineer, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Backend Engineer, you will design and evolve large-scale data architectures that support Copilot memory and personalization, spanning batch, streaming, and serving paths. You will build and operate high-quality personalization and memory data pipelines, including signal ingestion, normalization, enrichment, aggregation, memory generation, and full lifecycle management. You will enable memory and personalization features by exposing well-designed datasets, APIs, and feature interfaces for downstream product and ML consumers. You will work closely with PMs, applied ML, and product engineering to translate product intent into robust data systems and measurable outcomes. You will act as a technical leader for memory and personalization data systems, influencing architecture and standards across multiple teams. You will lead design reviews, unblock complex technical problems, and make principled trade-offs in ambiguous spaces.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Design and evolve large-scale data architectures that support Copilot memory and personalization, spanning batch, streaming, and serving paths.</li>\n<li>Build and operate high-quality personalization and memory data pipelines, including signal ingestion, normalization, enrichment, aggregation, memory generation, and full lifecycle management.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience building and deploying machine learning or large language model (LLM) applications at scale.</li>\n<li>Experience designing and implementing large-scale embedding, retrieval, and ranking systems.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.</li>\n<li>Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ebbb8b97-082","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-principal-backend-engineer-copilot-memory-and-personalization/","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"USD $139,900 – $274,800 per year or USD $163,000 – $296,400 per year","x-skills-required":["C","C++","C#","Java","JavaScript","Python","machine learning","large language model","embedding","retrieval","ranking"],"x-skills-preferred":["experience building and deploying machine learning or large language model (LLM) applications at scale","experience designing and implementing large-scale embedding, retrieval, and ranking systems"],"datePosted":"2026-03-06T07:31:16.271Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"C, C++, C#, Java, JavaScript, Python, machine learning, large language model, embedding, retrieval, ranking, experience building and deploying machine learning or large language model (LLM) applications at scale, experience designing and implementing large-scale embedding, retrieval, and ranking systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":296400,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2ab57edf-94a"},"title":"Senior Applied Scientist - Bing Search","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Beijing office. This role sits at the heart of Bing&#39;s search engine, managing tens of thousands of machines and delivering backend search services for document selection and ranking at massive scale.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist on the Bing Search Fundamental Team, you will be responsible for designing systems that can search through hundreds of billions of documents in just milliseconds. You will work alongside some of the brightest minds in the industry on projects that will make a lasting impact. Your expertise in Deep Learning, especially Natural Language Processing (NLP), will be crucial in driving best practices and common patterns across teams.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Expertise in Deep Learning, especially NLP, that power Bing search.</li>\n<li>Influence architecture and design decisions across teams, driving best practices and common patterns.</li>\n<li>Collaborate effectively with multiple teams, demonstrating solid partnership and communication skills.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor&#39;s Degree in Statistics, Computer Science, or related field AND 5+ years related experience (e.g., statistics predictive analytics, research) OR Master&#39;s Degree in Statistics, Computer Science, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Computer Science, or related field AND 3+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Expertise in deep learning, machine learning, NLP, or related areas.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Ability to think creatively and deliver innovative solutions to complex problems.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.</li>\n<li>Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2ab57edf-94a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-bing-search-2/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Deep Learning","Natural Language Processing","Machine Learning","Statistics","Predictive Analytics"],"x-skills-preferred":["Search technologies","Information retrieval"],"datePosted":"2026-03-06T07:30:38.683Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Beijing"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Deep Learning, Natural Language Processing, Machine Learning, Statistics, Predictive Analytics, Search technologies, Information retrieval"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b9fc94c7-edc"},"title":"Principal Product Manager - Publisher Content Marketplace","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Product Manager - Publisher Content Marketplace at their Redmond office. This role sits at the intersection of product, economics, and experimentation – ideal for a PM who enjoys building 0 to 1, is a self-starter and thrives in ambiguity.</p>\n<p><strong>About the Role</strong></p>\n<p>We&#39;re building a first-of-its-kind Content Marketplace that connects AI builders (LLMs, copilots, chatbots, enterprise AI apps) with high-quality content and data sources in real time. The marketplace enables LLMs to ground their responses in fresh, authoritative, and diverse content while ensuring publishers and creators are fairly rewarded. As a Principal Product Manager, you will define how AI systems access, value, and pay for grounding content, and ensure that marketplace pricing, policies, and performance are shaped by measurable demand-side outcomes.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Represent AI builder needs</li>\n<li>Act as the voice of AI builders in marketplace design – ensure the platform supports a wide range of grounding use cases (chatbots, copilots, enterprise bots, search models, etc.)</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Deep familiarity with LLM grounding, RAG systems, or data retrieval APIs.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Solid analytical and experimental mindset — experience running A/B or cluster experiments, defining metrics, and interpreting results.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Benefits and other compensation</li>\n<li>Professional development opportunities</li>\n<li>Financial benefits (bonus, equity, pension, etc.)</li>\n<li>Cultural perks (team events, office amenities, etc.)</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b9fc94c7-edc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-product-manager-publisher-content-marketplace/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"USD $139,900 – $274,800 per year","x-skills-required":["product management","software development","LLM grounding","RAG systems","data retrieval APIs"],"x-skills-preferred":["economics","data science","applied experimentation"],"datePosted":"2026-03-06T07:29:41.276Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"product management, software development, LLM grounding, RAG systems, data retrieval APIs, economics, data science, applied experimentation","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_bf73000c-a1a"},"title":"Member of Technical Staff - Principal Platform Engineer, Copilot Memory and Personalization","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Member of Technical Staff - Principal Platform Engineer, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Platform Engineer, you will design and build large-scale Copilot memory and personalization systems leveraging search, embeddings, retrieval, ranking, and Retrieval-Augmented Generation (RAG). You will apply subject-matter expertise in cross-product features, collaborating with appropriate stakeholders to drive project plans, release plans, and deliverables across multiple groups. You will hold accountability as a Designated Responsible Individual (DRI), mentoring engineers across products/solutions, working on-call to monitor system/product/service for degradation, downtime, or interruptions.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Design and build large-scale Copilot memory and personalization systems leveraging search, embeddings, retrieval, ranking, and Retrieval-Augmented Generation (RAG).</li>\n<li>Apply subject-matter expertise in cross-product features, collaborating with appropriate stakeholders to drive project plans, release plans, and deliverables across multiple groups.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience building and deploying machine learning or large language model (LLM) applications at scale.</li>\n<li>Experience designing and implementing large-scale embedding, retrieval, and ranking systems.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.</li>\n<li>Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_bf73000c-a1a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-principal-platform-engineer-copilot-memory-and-personalization/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"USD $139,900 – $274,800 per year","x-skills-required":["C","C++","C#","Java","JavaScript","Python","Machine learning","Large language model (LLM) applications","Embedding","Retrieval","Ranking"],"x-skills-preferred":["Experience building and deploying machine learning or large language model (LLM) applications at scale","Experience designing and implementing large-scale embedding, retrieval, and ranking systems"],"datePosted":"2026-03-06T07:28:54.767Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"C, C++, C#, Java, JavaScript, Python, Machine learning, Large language model (LLM) applications, Embedding, Retrieval, Ranking, Experience building and deploying machine learning or large language model (LLM) applications at scale, Experience designing and implementing large-scale embedding, retrieval, and ranking systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_741e1ef8-936"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Senior Applied Scientist at their Suzhou office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the AI and engineering system. You&#39;ll work directly with leadership to shape the company&#39;s direction in the global Office users market.</p>\n<p><strong>About the Role</strong></p>\n<p>We are seeking a highly skilled and motivated Applied Scientist with strong hands-on experience in building and optimizing agentic AI systems. Our mission is to benefit Office users with rich content and tool support to raise productivity, and we are building the AI and engineering system to make it happen. This position offers an exciting opportunity to design and develop highly complex and comprehensive systems combining engineering, AI and human participation. 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This position as an Applied Scientist II is for the modeling team, which builds machine learned models for predicting such events.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Designing and building efficient models for predicting user interactions with ads and advertiser’s pages.</li>\n<li>Designing and overseeing large-scale, long-term experiments to improve the health of the marketplace using advanced statistics and machine learning.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization and Bayesian inference.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Excellent problem solving and data analysis skills, effective communication skills, both verbal and written.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_631353ce-1c3","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/applied-scientist-ii-6/","x-work-arrangement":"onsite","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"USD $100,600 – $199,000 per year","x-skills-required":["statistical machine learning","deep learning","data mining","causal inference","information retrieval","game theory","mechanism design","optimization","Bayesian inference"],"x-skills-preferred":["experience in any of the following areas: statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization and Bayesian inference"],"datePosted":"2026-03-06T07:27:20.391Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization, Bayesian inference, experience in any of the following areas: statistical machine learning, deep learning, data mining, causal inference, information retrieval, game theory, mechanism design, optimization and Bayesian inference","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":100600,"maxValue":199000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_18b450e2-d82"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a highly skilled and motivated Applied Scientist with strong hands-on experience in building and optimizing agentic AI systems. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the AI market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist, you&#39;ll lead the science behind Discover&#39;s ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. You will set technical direction, mentor a high-caliber science cohort, and partner closely with engineering, PM, UXR, and policy to ship end-to-end outcomes.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Lead content-quality understanding at scale.</li>\n<li>Advance the recommendation &amp; ranking stack.</li>\n<li>Own evaluation and experimentation.</li>\n<li>Champion safety &amp; trust.</li>\n<li>Scale E2E ML systems.</li>\n<li>Mentor &amp; influence.</li>\n<li>Stay close to users.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>4+ years related experience (e.g., statistics predictive analytics, research).</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Expertise with LLMs (prompting, RAG, Parameter-Efficient Fine-Tuning), multimodal modeling, and retrieval-augmented recommendation.</li>\n<li>Familiarity with counterfactual learning and multi-objective optimization.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong communication and collaboration skills.</li>\n<li>Ability to work in a fast-paced environment.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9e63acec-fe1","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-7/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"CAD $114,400 – CAD $203,900 per year","x-skills-required":["LLMs","multimodal modeling","retrieval-augmented recommendation","counterfactual learning","multi-objective optimization"],"x-skills-preferred":["Python","PyTorch","TensorFlow"],"datePosted":"2026-03-06T07:25:39.633Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Vancouver"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, multimodal modeling, retrieval-augmented recommendation, counterfactual learning, multi-objective optimization, Python, PyTorch, TensorFlow","baseSalary":{"@type":"MonetaryAmount","currency":"CAD","value":{"@type":"QuantitativeValue","minValue":114400,"maxValue":203900,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6b47ab3c-965"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Redmond office. 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