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We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.</p>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>High-performance, large-scale distributed systems</li>\n<li>Implementing and deploying machine learning systems at scale</li>\n<li>Load balancing, request routing, or traffic management systems</li>\n<li>LLM inference optimization, batching, and caching strategies</li>\n<li>Kubernetes and cloud infrastructure (AWS, GCP)</li>\n<li>Python or Rust</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have significant software engineering experience, particularly with distributed systems</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Want to learn more about machine learning systems and infrastructure</li>\n<li>Thrive in environments where technical excellence directly drives both business results and research breakthroughs</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p>Representative projects across the org:</p>\n<ul>\n<li>Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators</li>\n<li>Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads</li>\n<li>Building production-grade deployment pipelines for releasing new models to millions of users</li>\n<li>Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage</li>\n<li>Contributing to new inference features (e.g., structured sampling, prompt caching)</li>\n<li>Supporting inference for new model architectures</li>\n<li>Analyzing observability data to tune performance based on real-world production workloads</li>\n<li>Managing multi-region deployments and geographic routing for global customers</li>\n</ul>\n<p>Deadline to apply: None. 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As a Staff Software Engineer, you will own large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Delivering experiments at a high velocity and level of quality to engage our customers</li>\n<li>Working across the entire product lifecycle from conceptualization through production</li>\n<li>Being able, and willing, to multi-task and learn new technologies quickly</li>\n</ul>\n<p>Ideally, you&#39;d have:</p>\n<ul>\n<li>7+ years of full-time engineering experience, post-graduation</li>\n<li>Experience scaling products at hyper growth startups</li>\n<li>Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies</li>\n<li>Proficient in Python or Javascript/Typescript, and SQL</li>\n<li>Experience with Kubernetes</li>\n<li>Experience with major cloud providers (AWS, Azure, GCP)</li>\n</ul>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. 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We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. 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The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems.</p>\n<p>You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Owning large new areas within our product</li>\n<li>Working across backend, frontend, and interacting with LLMs and ML models</li>\n<li>Delivering experiments at a high velocity and level of quality to engage our customers</li>\n<li>Working across the entire product lifecycle from conceptualization through production</li>\n</ul>\n<p>Ideally, you&#39;d have:</p>\n<ul>\n<li>4+ years of full-time engineering experience, post-graduation</li>\n<li>Experience scaling products at hyper growth startups</li>\n<li>Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies</li>\n<li>Proficient in Python or Javascript/Typescript, and SQL</li>\n<li>Experience with Kubernetes</li>\n<li>Experience with major cloud providers (AWS, Azure, GCP)</li>\n</ul>\n<p>Compensation packages at Scale for eligible roles include base salary, equity, and benefits. 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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. 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><strong>About Us</strong></p>\n<p>At Scale, our mission is to develop reliable AI systems for the world&#39;s most important decisions. 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. We are expanding our team to accelerate the development of AI applications.</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_78eea632-7b6","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/4623590005","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["Generative AI","Large Language Models (LLMs)","Agentic Frameworks","Machine Learning","Deep Learning","Applied Research","Distributed Systems","Real-time Data Processing"],"x-skills-preferred":["Text-to-SQL Systems","Multimodal AI","Reinforcement Learning (RL)","Reasoning and Planning","Agentic Systems","Vector Databases","Advanced Retrieval Techniques"],"datePosted":"2026-04-18T15:59:45.270Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Generative AI, Large Language Models (LLMs), Agentic Frameworks, Machine Learning, Deep Learning, Applied Research, Distributed Systems, Real-time Data Processing, Text-to-SQL Systems, Multimodal AI, Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems, Vector Databases, Advanced Retrieval Techniques","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6365e7d7-511"},"title":"Senior Forward Deployed Data Scientist/Engineer","description":"<p>We&#39;re hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment.</p>\n<p>This is not a traditional analytics role. 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. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.</p>\n<p>Responsibilities: Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities</p>\n<p>Requirements: 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans Strong foundation in statistics, experimentation, causal reasoning, and measurement Experience building tools or products, not just analyses , for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives High ownership and bias toward shipping in fast-moving environments with incomplete information</p>\n<p>Preferred qualifications: 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</p>\n<p>What success looks like: Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. 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 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"],"datePosted":"2026-04-18T15:59:44.618Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, SQL, 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_6f598f99-758"},"title":"Senior+ Software Engineer, Research Tools","description":"<p>We&#39;re looking for a Senior+ Software Engineer to join our Research Tools team. As a member of this team, you&#39;ll build the infrastructure and applications that enable our researchers to iterate quickly, run complex experiments, and extract insights from frontier AI systems.</p>\n<p>This role sits at the intersection of product thinking and full-stack engineering. You&#39;ll work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you&#39;re building human feedback interfaces for model evaluation, creating platforms for experiment orchestration, or developing novel visualization tools for understanding model behavior, your work will directly accelerate our mission to build safe, reliable AI systems.</p>\n<p>We&#39;re looking for someone who can operate with high agency in an ambiguous environment,someone who can be dropped into a research team, quickly develop domain expertise, and independently drive impactful projects from conception to delivery.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Build and maintain full-stack applications and infrastructure that researchers use daily to conduct experiments, collect feedback, and analyze results</li>\n<li>Partner closely with research teams to understand their workflows, pain points, and requirements, translating these into technical solutions</li>\n<li>Design intuitive interfaces and abstractions that make complex research tasks accessible and efficient</li>\n<li>Create reusable platforms and tools that accelerate the development of new research applications</li>\n<li>Rapidly prototype and iterate on solutions, gathering feedback from users and refining based on real-world usage</li>\n<li>Take ownership of complete product areas, from understanding user needs through design, implementation, and ongoing iteration</li>\n<li>Contribute to technical strategy and architectural decisions for research tooling</li>\n<li>Mentor other engineers and help establish best practices for research application development</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>5+ years of software engineering experience with a strong focus on full-stack development</li>\n<li>Excel at rapid iteration and shipping,you can move from concept to working prototype quickly</li>\n<li>Have experience building tools, platforms, or infrastructure for technical users (engineers, researchers, data scientists, analysts, etc.)</li>\n<li>Demonstrate high agency and ability to operate independently in ambiguous environments</li>\n<li>Can quickly develop deep understanding of complex technical domains</li>\n<li>Have strong product instincts and can identify the right problems to solve</li>\n<li>Are proficient with modern web technologies (React, TypeScript, Python, etc.)</li>\n<li>Have a track record of building user-facing applications that are actually used and loved by their target audience</li>\n<li>Communicate effectively with both technical and non-technical stakeholders</li>\n<li>Care about the societal impacts of your work and are motivated by Anthropic&#39;s mission</li>\n</ul>\n<p>Strong candidates may also have:</p>\n<ul>\n<li>Experience building research tools, scientific software, or experimentation platforms</li>\n<li>Background in machine learning, AI research, or working closely with ML researchers</li>\n<li>Founded or been an early engineer at a startup, particularly one focused on developer or researcher tools</li>\n<li>Built open-source tools or platforms with active user communities</li>\n<li>Experience with data visualization, interactive interfaces, or novel interaction paradigms</li>\n<li>Contributed to engineering platforms or internal tooling at scale (similar to Heroku, Vercel, or other platform-as-a-service products)</li>\n<li>Experience leveraging AI/LLMs to build more powerful or efficient tools</li>\n<li>Previous work in creative tools, artist tools, or other domains requiring deep user empathy</li>\n<li>Domain knowledge in areas like human-computer interaction, systems safety, or AI alignment</li>\n</ul>\n<p>Annual compensation range for this role is $300,000-$405,000 USD.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a 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interaction","systems safety","AI alignment"],"datePosted":"2026-04-18T15:59:42.608Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"full-stack development, modern web technologies, React, TypeScript, Python, rapid iteration, shipping, product instincts, problem-solving, communication, societal impacts, research tools, scientific software, experimentation platforms, machine learning, AI research, open-source tools, data visualization, interactive interfaces, novel interaction paradigms, engineering platforms, internal tooling, AI/LLMs, creative tools, artist tools, human-computer interaction, systems safety, AI alignment","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_853e1417-019"},"title":"Solutions Architect, Applied AI (National Security)","description":"<p>As a Solutions Architect, Applied AI (National Security), you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping national security and defense agencies understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack.</p>\n<p>You will combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability.</p>\n<p>Working closely with our Sales, Product, and Engineering teams, you&#39;ll guide customers from initial technical discovery through successful deployment. You&#39;ll leverage your expertise to help customers understand Claude&#39;s capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation</li>\n</ul>\n<ul>\n<li>Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams &amp; stakeholders to drive customer success</li>\n</ul>\n<ul>\n<li>Support customers building with Claude Code, the Claude API, and Claude for Enterprise</li>\n</ul>\n<ul>\n<li>Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering &amp; development teams up to business value focused conversations with executives</li>\n</ul>\n<ul>\n<li>Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack</li>\n</ul>\n<ul>\n<li>Help customers develop evaluation frameworks to measure Claude&#39;s performance for their specific use cases</li>\n</ul>\n<ul>\n<li>Identify common integration patterns and contribute insights back to our Product and Engineering teams</li>\n</ul>\n<ul>\n<li>Travel frequently to customer sites for workshops, technical deep dives, and relationship building</li>\n</ul>\n<ul>\n<li>Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns</li>\n</ul>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li>TS/SCI clearance required</li>\n</ul>\n<ul>\n<li>Must have prior experience working with US national security (defense and/or intelligence) agencies</li>\n</ul>\n<ul>\n<li>5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager</li>\n</ul>\n<ul>\n<li>Experience navigating complex buying cycles involving multiple stakeholders</li>\n</ul>\n<ul>\n<li>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering &amp; IT teams, and more</li>\n</ul>\n<ul>\n<li>Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders</li>\n</ul>\n<ul>\n<li>Experience designing scalable cloud architectures and integrating with enterprise systems</li>\n</ul>\n<ul>\n<li>Familiar with Python</li>\n</ul>\n<ul>\n<li>Familiarity with common LLM frameworks and tools or a background in machine learning or data science</li>\n</ul>\n<ul>\n<li>Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>\n</ul>\n<ul>\n<li>A love of teaching, mentoring, and helping others succeed</li>\n</ul>\n<ul>\n<li>Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>\n</ul>\n<ul>\n<li>Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems</li>\n</ul>\n<p>The annual compensation range for this role is $240,000-$270,000 USD.</p>\n<p>Logistics:</p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n</ul>\n<ul>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n</ul>\n<ul>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<p>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.</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>How we&#39;re different:</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: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p>Come work with us!</p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to</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_853e1417-019","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5079511008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$240,000-$270,000 USD","x-skills-required":["TS/SCI clearance","Prior experience working with US national security (defense and/or intelligence) agencies","Technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager","Experience navigating complex buying cycles involving multiple stakeholders","Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders","Experience designing scalable cloud architectures and integrating with enterprise systems","Familiar with Python","Familiarity with common LLM frameworks and tools or a background in machine learning or data science"],"x-skills-preferred":["Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more","Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities","A love of teaching, mentoring, and helping others succeed","Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders","Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems"],"datePosted":"2026-04-18T15:59:41.597Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Washington, DC"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"TS/SCI clearance, Prior experience working with US national security (defense and/or intelligence) agencies, Technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager, Experience navigating complex buying cycles involving multiple stakeholders, Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders, Experience designing scalable cloud architectures and integrating with enterprise systems, Familiar with Python, Familiarity with common LLM frameworks and tools or a background in machine learning or data science, Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more, Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities, A love of teaching, mentoring, and helping others succeed, Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders, Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":240000,"maxValue":270000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3aedc59f-428"},"title":"Senior Forward Deployed AI Engineer, Enterprise","description":"<p>As a Senior Forward Deployed AI Engineer on our Enterprise team, you&#39;ll be the technical bridge between Scale AI&#39;s cutting-edge AI capabilities and our most strategic customers. You&#39;ll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.</p>\n<p>This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You&#39;ll work directly with customer engineering teams to integrate AI into their critical workflows.</p>\n<p><strong>Key Responsibilities</strong></p>\n<p><strong>Customer Integration &amp; Deployment</strong></p>\n<ul>\n<li>Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements</li>\n<li>Design and implement custom integrations between Scale AI&#39;s platform and customer data environments (cloud platforms, data warehouses, internal APIs)</li>\n<li>Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows</li>\n<li>Deploy and configure AI models and agents within customer security and compliance boundaries</li>\n</ul>\n<p><strong>AI Agent Development</strong></p>\n<ul>\n<li>Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation</li>\n<li>Architect multi-agent systems that orchestrate between different models, tools, and data sources</li>\n<li>Implement evaluation frameworks to measure agent performance and iterate toward business objectives</li>\n<li>Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement</li>\n</ul>\n<p><strong>Prompt Engineering &amp; Optimization</strong></p>\n<ul>\n<li>Create sophisticated prompt engineering strategies optimized for customer-specific domains and data</li>\n<li>Build and maintain prompt libraries, templates, and best practices for customer use cases</li>\n<li>Conduct systematic prompt experimentation and A/B testing to improve model outputs</li>\n<li>Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate</li>\n</ul>\n<p><strong>Technical Leadership &amp; Collaboration</strong></p>\n<ul>\n<li>Serve as the primary technical point of contact for strategic enterprise accounts</li>\n<li>Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration</li>\n<li>Provide technical training and knowledge transfer to customer teams</li>\n<li>Work closely with Scale&#39;s product and engineering teams to translate customer needs into product improvements</li>\n<li>Document technical architectures, integration patterns, and best practices</li>\n</ul>\n<p><strong>Problem Solving &amp; Innovation</strong></p>\n<ul>\n<li>Debug complex technical issues across the entire stack, from data pipelines to model outputs</li>\n<li>Rapidly prototype solutions to unblock customers and prove out new use cases</li>\n<li>Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems</li>\n<li>Identify opportunities for productization based on common customer patterns</li>\n</ul>\n<p><strong>Required Qualifications</strong></p>\n<ul>\n<li>4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design</li>\n<li>Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)</li>\n<li>Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure</li>\n<li>Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions</li>\n<li>Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Agent Development Wiz</li>\n<li>Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures</li>\n<li>Experience building and deploying AI agents or autonomous systems in production</li>\n<li>Knowledge of vector databases and semantic search systems</li>\n<li>Contributions to open-source AI/ML projects</li>\n</ul>\n<ul>\n<li>Infrastructure Guru</li>\n<li>Experience with containerization (Docker, Kubernetes) and CI/CD pipelines</li>\n<li>Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools</li>\n<li>Previous work in a devops, platform, or infra role</li>\n</ul>\n<ul>\n<li>Customer Product Whisperer</li>\n<li>Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role</li>\n<li>Domain expertise in verticals like finance, healthcare, government, or manufacturing</li>\n<li>Experience with technical enablement or teaching programs</li>\n</ul>\n<p><strong>Sample Projects</strong></p>\n<p>The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.</p>\n<ul>\n<li>Deep Research for Due Diligence</li>\n<li>Churn Prediction</li>\n<li>Data Extraction Voice Agent</li>\n</ul>\n<p><strong>Compensation</strong></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><strong>Pay Transparency</strong></p>\n<p>For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000-$270,000 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_3aedc59f-428","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/4597399005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,000-$270,000 USD","x-skills-required":["Software engineering","Data structures","Algorithms","System design","Python","ML/AI frameworks","Cloud platforms","Modern data infrastructure","Problem-solving","Communication"],"x-skills-preferred":["LLMs","Prompting techniques","Embeddings","RAG architectures","Containerization","CI/CD pipelines","Infrastructure as Code","Devops","Platform","Infra"],"datePosted":"2026-04-18T15:59:30.214Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Software engineering, Data structures, Algorithms, System design, Python, ML/AI frameworks, Cloud platforms, Modern data infrastructure, Problem-solving, Communication, LLMs, Prompting techniques, Embeddings, RAG architectures, Containerization, CI/CD pipelines, Infrastructure as Code, Devops, Platform, Infra","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216000,"maxValue":270000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_539e2a23-ddf"},"title":"Tech Lead Manager- MLRE, ML Systems","description":"<p>You will lead the development of our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline.</p>\n<p>You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimising the platform to enable our next generation LLM training, inference and data curation.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Building, profiling and optimising our training and inference framework.</li>\n<li>Collaborating with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.</li>\n<li>Researching and integrating state-of-the-art technologies to optimise our ML system.</li>\n</ul>\n<p>The ideal candidate will have:</p>\n<ul>\n<li>Passionate about system optimisation.</li>\n<li>Experience with multi-node LLM training and inference.</li>\n<li>Experience with developing large-scale distributed ML systems.</li>\n<li>Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.</li>\n<li>Strong software engineering skills, proficient in frameworks and tools such as CUDA, PyTorch, transformers, flash attention, etc.</li>\n</ul>\n<p>Nice to haves include demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.</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.</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_539e2a23-ddf","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4618046005","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$264,800-$331,000 USD","x-skills-required":["system optimisation","multi-node LLM training and inference","large-scale distributed ML systems","post-training methods","software engineering skills","CUDA","PyTorch","transformers","flash attention"],"x-skills-preferred":["next generation use cases for large language models","instruction tuning","RLHF","tool use","reasoning","agents","multimodal"],"datePosted":"2026-04-18T15:59:21.558Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"system optimisation, multi-node LLM training and inference, large-scale distributed ML systems, post-training methods, software engineering skills, CUDA, PyTorch, transformers, flash attention, next generation use cases for large language models, instruction tuning, RLHF, tool use, reasoning, agents, multimodal","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":264800,"maxValue":331000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0f6f3674-ac6"},"title":"Director, Enterprise Machine Learning & Research","description":"<p>The Enterprise ML team at Scale works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale&#39;s proprietary research, data, and infrastructure.</p>\n<p>As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.</p>\n<p>This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Leading, mentoring, and growing a team of research scientists and engineers working on GenAI research initiatives</li>\n<li>Defining and driving a multi-year research roadmap, identifying key scientific questions, setting milestones, allocating resources, and ensuring rigorous execution</li>\n<li>Collaborating cross-functionally with engineering, product, client-facing teams, and external academic or industry partners to translate research into components, insights, and actionable outcomes</li>\n<li>Communicating compellingly, publishing research, presenting at conferences, engaging in open-source contributions, and representing the team externally</li>\n<li>Driving an inclusive, high-performing culture, helping your team through technical challenges, providing growth opportunities, and attracting top talent</li>\n</ul>\n<p>Core qualifications include:</p>\n<ul>\n<li>8+ years of hands-on research experience in machine learning, deep learning, generative models, agent/RL systems, or related domains</li>\n<li>A strong track record of research excellence, including publications in top-tier ML/AI venues</li>\n<li>Experience leading or managing research teams</li>\n<li>Excellent written and verbal communication skills</li>\n</ul>\n<p>Nice-to-have qualifications include:</p>\n<ul>\n<li>Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments</li>\n<li>Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale</li>\n<li>Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes</li>\n</ul>\n<p>Compensation packages at Scale include base salary, equity, and benefits, with a salary range of $289,800-$362,250 USD for this full-time position in San Francisco, New York, and Seattle.</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_0f6f3674-ac6","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/4679727005","x-work-arrangement":"onsite","x-experience-level":"executive","x-job-type":"full-time","x-salary-range":"$289,800-$362,250 USD","x-skills-required":["machine learning","deep learning","generative models","agent/RL systems","research leadership","team management","communication","public speaking","writing","open-source contributions"],"x-skills-preferred":["hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments","prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale","proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes"],"datePosted":"2026-04-18T15:59:19.457Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, generative models, agent/RL systems, research leadership, team management, communication, public speaking, writing, open-source contributions, hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments, prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale, proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":289800,"maxValue":362250,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5aa5b947-f4d"},"title":"Staff Machine Learning Research Scientist/ Engineer, Agents","description":"<p>About Scale AI</p>\n<p>At Scale AI, our mission is to accelerate the development of AI applications. This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation.</li>\n<li>Contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow.</li>\n<li>A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.).</li>\n<li>At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.</li>\n</ul>\n<p>Nice to Have</p>\n<ul>\n<li>Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax.</li>\n<li>Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.</li>\n<li>Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.</li>\n<li>Familiarity with agentic reasoning methods such as STaR and PLANSEARCH</li>\n<li>Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.</li>\n</ul>\n<p>Benefits</p>\n<ul>\n<li>Comprehensive health, dental and vision coverage</li>\n<li>Retirement benefits</li>\n<li>A learning and development stipend</li>\n<li>Generous PTO</li>\n<li>Commuter stipend</li>\n</ul>\n<p>Salary Range</p>\n<p>$259,200-$324,000 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_5aa5b947-f4d","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/4488520005","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$259,200-$324,000 USD","x-skills-required":["Pytorch","Jax","Tensorflow","LLMs","Agent frameworks","Agentic reasoning methods","Cloud technology stack"],"x-skills-preferred":["Open source LLM fine-tuning","Bespoke LLM fine-tuning projects"],"datePosted":"2026-04-18T15:59:17.656Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Pytorch, Jax, Tensorflow, LLMs, Agent frameworks, Agentic reasoning methods, Cloud technology stack, Open source LLM fine-tuning, Bespoke LLM fine-tuning projects","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":259200,"maxValue":324000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ddc03b8a-992"},"title":"Sr. Engineering Manager - Lakeflow Designer","description":"<p>At Databricks, we are building the world&#39;s best data and AI infrastructure platform to enable data teams to solve the world&#39;s toughest problems. The Authoring team at Databricks builds the main user experience which drives the workloads for most of the company&#39;s revenue. Within this organization, the Lakeflow Designer team is on a mission to enable less technical users to transform data with ease through a low-code and AI-first experience.</p>\n<p>As the Engineering Manager for Lakeflow Designer, you will lead a seed team of engineers to build a brand new Visual and AI-first editing experience for Databricks SQL. You will play a pivotal role in bringing this product from its current Private Preview stage to General Availability (GA) in the next 6-9 months. You will be responsible for scaling the team from its current size of ~6 engineers to 10-15 over the next year.</p>\n<p>This is a high-visibility frontend-focused role where you will guide the development of intuitive user experiences and embedded agentic assistants that have the potential to completely change how customers interact with and analyze data on the platform.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Leading product launch: Drive the roadmap and execution to launch Lakeflow Designer to General Availability (GA) within 6-9 months, ensuring we bring the product to market and delight users.</li>\n<li>Scaling the team: Rapidly hire and build out the team in a fast-moving area, growing the engineering headcount to 10-15 members.</li>\n<li>Driving technical &amp; UX strategy: Oversee a frontend-heavy technology stack (React, TypeScript), championing high-quality UX and the integration of Gen AI/LLMs to build agentic capabilities.</li>\n<li>Unlocking data insights: Build an experience that opens up the platform to a broader, less technical audience, enabling entire new categories of customers to get insights from their data.</li>\n<li>Cross-functional collaboration: Partner closely with a strong Technical Lead, Product Management, and Design team to define the product vision and ensure successful execution.</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>10+ years of software engineering experience, with a strong track record of technical leadership and impact.</li>\n<li>5+ years of Engineering Leadership: Experience leading frontend teams, with a proven ability to manage and grow high-performing engineering groups.</li>\n<li>Frontend expertise: Strong technical background in React, TypeScript, and JavaScript.</li>\n<li>Product &amp; UX passion: A strong passion for product and user experience; you care deeply about how users interact with the tool.</li>\n<li>Zero-to-one experience: Experience bringing a product from &#39;zero to one&#39; is a significant plus.</li>\n<li>AI/LLM interest: Experience building Agents and working with LLMs is a bonus.</li>\n<li>Fast-paced execution: Ability to thrive in a fast-moving environment, specifically with experience hiring and scaling teams rapidly.</li>\n</ul>\n<p>Why join us?</p>\n<ul>\n<li>Redefine SQL authoring: SQL is the main way our customers interact with their data; this role offers the chance to completely change how customers write SQL across the Databricks platform.</li>\n<li>Intersection of AI and UX: Work at the cutting edge of Gen AI, building agentic assistants that genuinely simplify complex workflows.</li>\n<li>High impact: Lead a team that is building a product with the potential to unlock data insights for vastly more users than what is possible today with raw SQL or notebooks.</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_ddc03b8a-992","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/5627916002","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["React","TypeScript","JavaScript","Frontend engineering","Leadership","Product management","User experience design"],"x-skills-preferred":["Gen AI","LLMs","Agentic assistants","Zero-to-one product development"],"datePosted":"2026-04-18T15:59:12.125Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bellevue, Washington; Seattle, Washington"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"React, TypeScript, JavaScript, Frontend engineering, Leadership, Product management, User experience design, Gen AI, LLMs, Agentic assistants, Zero-to-one product development"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_7d4c3fc5-2ed"},"title":"Senior Software Engineer, Inference","description":"<p>About the role:</p>\n<p>Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry&#39;s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.</p>\n<p>The team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.</p>\n<p>Strong candidates may also have experience with:</p>\n<ul>\n<li>High-performance, large-scale distributed systems</li>\n<li>Implementing and deploying machine learning systems at scale</li>\n<li>Load balancing, request routing, or traffic management systems</li>\n<li>LLM inference optimization, batching, and caching strategies</li>\n<li>Kubernetes and cloud infrastructure (AWS, GCP)</li>\n<li>Python or Rust</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>Have significant software engineering experience, particularly with distributed systems</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Want to learn more about machine learning systems and infrastructure</li>\n<li>Thrive in environments where technical excellence directly drives both business results and research breakthroughs</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p>Representative projects across the org:</p>\n<ul>\n<li>Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators</li>\n<li>Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads</li>\n<li>Building production-grade deployment pipelines for releasing new models to millions of users</li>\n<li>Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage</li>\n<li>Contributing to new inference features (e.g., structured sampling, prompt caching)</li>\n<li>Supporting inference for new model architectures</li>\n<li>Analyzing observability data to tune performance based on real-world production workloads</li>\n<li>Managing multi-region deployments and geographic routing for global customers</li>\n</ul>\n<p>Annual compensation range for this role is €235,000-€295,000 EUR.</p>\n<p>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>\n<p>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</p>\n<p>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</p>\n<p>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.</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>How we&#39;re different:</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: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p>Come work with us!</p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.</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_7d4c3fc5-2ed","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4641822008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"€235,000-€295,000 EUR","x-skills-required":["High-performance, large-scale distributed systems","Implementing and deploying machine learning systems at scale","Load balancing, request routing, or traffic management systems","LLM inference optimization, batching, and caching strategies","Kubernetes and cloud infrastructure (AWS, GCP)","Python or Rust"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:59:09.302Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dublin, IE"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"High-performance, large-scale distributed systems, Implementing and deploying machine learning systems at scale, Load balancing, request routing, or traffic management systems, LLM inference optimization, batching, and caching strategies, Kubernetes and cloud infrastructure (AWS, GCP), Python or Rust","baseSalary":{"@type":"MonetaryAmount","currency":"EUR","value":{"@type":"QuantitativeValue","minValue":235000,"maxValue":295000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fb1f459e-b3a"},"title":"Machine Learning Research Scientist / Engineer, Reasoning","description":"<p>About Scale</p>\n<p>At Scale, our mission is to accelerate the development of AI applications. We&#39;re looking for a Machine Learning Research Scientist/Engineer to join our team and help us shape the future of AI.</p>\n<p>This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). You will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale&#39;s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning.</p>\n<p>Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.</p>\n<p>Responsibilities</p>\n<ul>\n<li>Study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents</li>\n<li>Shape Scale&#39;s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning</li>\n<li>Contribute to impactful research on language model reasoning</li>\n<li>Collaborate with external researchers</li>\n<li>Work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions</li>\n</ul>\n<p>Requirements</p>\n<ul>\n<li>Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow</li>\n<li>A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.)</li>\n<li>At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning</li>\n<li>Strong written and verbal communication skills, along with the ability to work effectively across teams</li>\n</ul>\n<p>Nice to Have</p>\n<ul>\n<li>Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX</li>\n<li>Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents</li>\n<li>Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar</li>\n<li>Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH</li>\n<li>Proficiency in cloud-based ML development, with experience in AWS or GCP environments</li>\n</ul>\n<p>Benefits</p>\n<ul>\n<li>Comprehensive health, dental and vision coverage</li>\n<li>Retirement benefits</li>\n<li>A learning and development stipend</li>\n<li>Generous PTO</li>\n<li>Commuter stipend</li>\n</ul>\n<p>Salary Range</p>\n<p>$252,000-$315,000 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_fb1f459e-b3a","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/4605596005","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$252,000-$315,000 USD","x-skills-required":["PyTorch","JAX","TensorFlow","Large Language Models (LLMs)","Planning Algorithms","Agentic Reasoning","Data Generation","Model Interaction","Evaluation"],"x-skills-preferred":["Agent Frameworks","Cloud-Based ML Development","AWS","GCP","STaR","PLANSEARCH"],"datePosted":"2026-04-18T15:59:07.207Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; Seattle, WA; New York, NY"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PyTorch, JAX, TensorFlow, Large Language Models (LLMs), Planning Algorithms, Agentic Reasoning, Data Generation, Model Interaction, Evaluation, Agent Frameworks, Cloud-Based ML Development, AWS, GCP, STaR, PLANSEARCH","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":252000,"maxValue":315000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_770c5fe8-cce"},"title":"Staff Security Engineer, Vulnerability Management","description":"<p>We are seeking a Staff Security Engineer to lead the most complex technical work in CoreWeave&#39;s Vulnerability Management program.</p>\n<p>As a Staff Security Engineer, you will design and implement scalable triage, prioritization, and remediation-tracking systems across application, infrastructure, and hardware domains. You will set technical standards, drive high-impact initiatives, and mentor engineers through technical leadership, while partnering with leadership on priorities and execution risks.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Lead high-complexity VM technical initiatives and deliver architecture decisions for assigned program areas</li>\n<li>Design and build scalable triage automation, including integrations, decision logic, and production hardening</li>\n<li>Implement end-to-end workflow components from assessment and detection to ticket routing and remediation tracking</li>\n<li>Provide deep technical leadership on hardware-adjacent vulnerabilities (GPU firmware, DPU firmware/BlueField, and BMC surfaces)</li>\n<li>Act as senior technical responder for embargoed disclosures and zero-day events, coordinating with owner teams that deploy fixes</li>\n<li>Improve prioritization logic, severity models, and exception workflows through code, design reviews, and technical proposals</li>\n<li>Produce actionable technical metrics and risk insights for leadership consumption</li>\n<li>Lead root-cause analysis for high-impact vulnerability incidents and implement durable technical improvements</li>\n<li>Mentor IC3/IC4/IC5 engineers through design guidance, code review, and incident coaching</li>\n<li>Partner with security, engineering, and operational stakeholders to improve workflow reliability and accelerate remediation outcomes</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>9+ years of relevant experience with demonstrated strategic impact in vulnerability management, application security, platform security, or cloud security engineering</li>\n<li>Proven track record building and scaling security automation (SOAR workflows, AI/ML systems, detection pipelines) in production environments</li>\n<li>Deep subject matter expertise with vulnerability management best practices: CVSS, EPSS, CISA KEV, threat intelligence integration, and risk-based prioritization frameworks</li>\n<li>Excellent development background with strong coding skills in Python, Go, or similar languages for building scalable, production-grade security systems</li>\n<li>Significant experience with modern vulnerability management tooling (for example Wiz, Semgrep, Rapid7, Tenable, or equivalent)</li>\n<li>Experience with specialized infrastructure: GPU/DPU environments, firmware security, hardware vulnerabilities, or high-performance computing</li>\n<li>Demonstrated track record mentoring engineers across levels and driving cross-functional technical initiatives at organizational scale</li>\n<li>Strong business acumen and understanding of how security decisions impact engineering velocity, customer trust, and business outcomes</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Practical experience building AI/ML-powered security systems (LLM integration, automated decision-making, human-in-the-loop validation) in production</li>\n<li>Experience managing hardware vendor security partnerships (embargoed disclosures and pre-release collaboration)</li>\n<li>Production experience with security automation platforms such as TINES and serverless frameworks (AWS Lambda, GCP Cloud Functions)</li>\n<li>Strong DevOps, DevSecOps, or SRE background with deep experience in AWS/GCP/Azure cloud services and Infrastructure as Code (Terraform, CloudFormation)</li>\n<li>Deep understanding of Kubernetes security (container scanning, admission controllers, supply chain security, runtime protection)</li>\n<li>Experience leading security programs through rapid hypergrowth (10x+ infrastructure scaling) in startup or cloud-native environments</li>\n<li>Practical experience managing vulnerabilities within a FedRAMP-certified environment or similar regulatory frameworks</li>\n</ul>\n<p>Salary and Benefits: The base salary range for this role is $188,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).</p>\n<p>Work Environment:</p>\n<p>While we prioritize a hybrid work environment, remote work may be considered for candidates located more than 30 miles from an office, based on role requirements for specialized skill sets. New hires will be invited to attend onboarding at one of our hubs within their first month. Teams also gather quarterly to support collaboration.</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_770c5fe8-cce","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/4653130006","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$188,000 to $275,000","x-skills-required":["vulnerability management","application security","platform security","cloud security engineering","security automation","AI/ML systems","detection pipelines","Python","Go","modern vulnerability management tooling","GPU/DPU environments","firmware security","hardware vulnerabilities","high-performance computing"],"x-skills-preferred":["AI/ML-powered security systems","LLM integration","automated decision-making","human-in-the-loop validation","security automation platforms","TINES","serverless frameworks","AWS Lambda","GCP Cloud Functions","DevOps","DevSecOps","SRE","Kubernetes security","container scanning","admission controllers","supply chain security","runtime protection"],"datePosted":"2026-04-18T15:59:06.360Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Livingston, NJ / New York, NY / Sunnyvale, CA / Bellevue, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"vulnerability management, application security, platform security, cloud security engineering, security automation, AI/ML systems, detection pipelines, Python, Go, modern vulnerability management tooling, GPU/DPU environments, firmware security, hardware vulnerabilities, high-performance computing, AI/ML-powered security systems, LLM integration, automated decision-making, human-in-the-loop validation, security automation platforms, TINES, serverless frameworks, AWS Lambda, GCP Cloud Functions, DevOps, DevSecOps, SRE, Kubernetes security, container scanning, admission controllers, supply chain security, runtime protection","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":188000,"maxValue":275000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5d71bfd7-723"},"title":"Partner Solutions Architect, Applied AI","description":"<p>As a Partner Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP).</p>\n<p>You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Strategic Technical Partnership: Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues.</li>\n</ul>\n<ul>\n<li>Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment</li>\n</ul>\n<ul>\n<li>Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance.</li>\n</ul>\n<ul>\n<li>Partner Ecosystem &amp; Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.</li>\n</ul>\n<p>Product Feedback: Validate and gather feedback on Anthropic&#39;s products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy.</p>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li>5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager</li>\n</ul>\n<ul>\n<li>Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery</li>\n</ul>\n<ul>\n<li>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering &amp; IT teams, and more</li>\n</ul>\n<ul>\n<li>Strong presentation &amp; technical communication skills with the ability to translate requirements between technical and business stakeholders</li>\n</ul>\n<ul>\n<li>Experience designing scalable cloud architectures and integrating with enterprise systems</li>\n</ul>\n<ul>\n<li>Familiarity with common LLM frameworks and tools or a background in machine learning or data science</li>\n</ul>\n<ul>\n<li>Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>\n</ul>\n<ul>\n<li>A love of teaching, mentoring, and helping others succeed</li>\n</ul>\n<ul>\n<li>Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems</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_5d71bfd7-723","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5112486008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["technical customer-facing/partner-facing roles","Solutions Architect","Sales Engineer","Partner Sales Engineer","Technical Account Manager","cloud providers","scalable cloud architectures","enterprise systems","LLM frameworks","machine learning","data science"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:59:03.769Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris, France"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"technical customer-facing/partner-facing roles, Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager, cloud providers, scalable cloud architectures, enterprise systems, LLM frameworks, machine learning, data science"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_057b8651-835"},"title":"AI Strategy Consultant, Frontier Tech","description":"<p>As a member of our Frontier Tech Consultant team, you will play a critical role in advancing cutting-edge AI innovations by conducting high-impact experiments and ensuring seamless execution at the highest quality standards.</p>\n<p>Your work will directly contribute to Scale AI’s growth, shaping the future of artificial intelligence. In this role, you will be working on various types of projects, including but not limited to: research experiments, dataset generation, data quality improvements, and in-depth technical analysis.</p>\n<p>You will tackle complex, technical and operational challenges while collaborating closely with Scale’s ML research scientists and SPM team.</p>\n<p>The ideal candidate is analytical, detail-oriented, and results-driven, with strong problem-solving abilities and excellent communication skills.</p>\n<p>We are looking for someone who thrives in a fast-paced environment, is proactive in overcoming challenges, and is committed to delivering exceptional outcomes.</p>\n<p>If you are eager to contribute to the forefront of AI innovation, we encourage you to apply.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and execute research experiments</li>\n<li>Build and evaluate frontier LLM datasets</li>\n<li>Develop training and testing material for frontier pipelines</li>\n<li>Improve quality of existing and new products</li>\n</ul>\n<p>Ideally you’d have:</p>\n<ul>\n<li>Strong machine learning knowledge, either by being in the final years of a ML PhD career or having already graduated</li>\n<li>Strong writing and verbal communication skills</li>\n<li>An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results</li>\n<li>Analytical, planning, and process improvement capability</li>\n<li>Experience working in a fast-paced, entrepreneurial environment</li>\n<li>Technical skills including familiarity with Python, GPU, AWS, API, LLM, ML, and SQL</li>\n</ul>\n<p>Pay: $60-80/hr</p>\n<p>Commitment: This is a fully remote, US-based part-time (10-20 hours per week), on-going contract position staffed via HireArt.</p>\n<p>HireArt values diversity and is an Equal Opportunity Employer. We are interested in every qualified candidate who is eligible to work in the United States. Unfortunately, we are not able to sponsor visas, including CPT/OPT or employ corp-to-corp.</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_057b8651-835","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4472223005","x-work-arrangement":"remote","x-experience-level":null,"x-job-type":"contract","x-salary-range":"$60-80/hr","x-skills-required":["Python","GPU","AWS","API","LLM","ML","SQL"],"x-skills-preferred":["Machine Learning","Data Analysis","Problem Solving"],"datePosted":"2026-04-18T15:59:01.983Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"jobLocationType":"TELECOMMUTE","employmentType":"CONTRACTOR","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, GPU, AWS, API, LLM, ML, SQL, Machine Learning, Data Analysis, Problem Solving"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d4705425-01c"},"title":"Technical Deployment Lead, Applied AI","description":"<p>As a Technical Deployment Lead on the Claude Agentic Solutions team, you will lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries.</p>\n<p>You&#39;ll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes. This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion.</p>\n<p>You will champion our mission in the field, ensure world-class delivery, and bring insights back to our product and research teams on a regular basis. You&#39;ll own engagements end-to-end, from SOW through production deployment.</p>\n<p>You&#39;ll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organisational complexity that comes with deploying AI agents in enterprise environments.</p>\n<p>You need to be technical enough to hold architecture conversations with engineering stakeholders and polished enough to represent Anthropic to high-level executives in high-stakes environments.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Manage the technical delivery plan for each engagement.</li>\n<li>Structure the SOW by clearly defining the scope, steps, dependencies, success criteria, and value hypotheses.</li>\n<li>Translate customer commercial objectives into a sequenced roadmap that our FDEs execute.</li>\n<li>Supervise technical discovery: map customer workflows, identify constraints, define the MVP, and shape the solution architecture for custom agent deployments.</li>\n<li>Lead the execution and delivery of daily engineering work within Anthropic and customer teams. Ensure project progress is smooth and sequenced. Make real-time trade-offs on scope and priority to preserve the critical path.</li>\n<li>Ensure product scope for field missions: define the MVP, write requirements documentation, prioritise the engineering backlog, and manage scope against success criteria as requirements evolve. Manage the кури relationship throughout delivery. Organise executive briefings, manage communications with stakeholders regarding technical leads and supply, and represent Anthropic to high-level commercial and technical executives in terms of technical credibility.</li>\n<li>Measure value and ROI: define impact hypotheses, establish baselines and key performance indicators, conduct pre- and post-deployment measurements, and communicate results to executive sponsors.</li>\n<li>Codify reusable solution patterns, evaluation frameworks, and technical manuals.</li>\n<li>Record best practices from various interactions and transmit signals from the field to Product and Research teams to improve our platform and models.</li>\n<li>Navigate enterprise and regulatory complexity: security audits, legal approvals, procurement processes, compliance requirements, and organisational dynamics.</li>\n<li>Manage scope and change: manage evolving requirements, define expectations, negotiate contract modifications, identify risks upfront, and signal them with clear context, as needed.</li>\n<li>Manage delivery operations: sprint ceremonies, review milestones, and progress reports.</li>\n<li>Visit customer sites to build relationships, unlock deliveries, and accelerate adoption (target 25-50%).</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>More than 5 years of technical leadership experience with customers. This can include technical engagement management, technical program management, or technical product management, in startups/founders, technical profiles, professional services, consulting, or enterprise software.</li>\n<li>Have deployed AI agent-based solutions using AI, ML, or LLM. You understand applicable models, integration approaches, and real-world realities.</li>\n<li>Be able to hold architecture conversations with engineering stakeholders, evaluate technical trade-offs, and test technical decisions under pressure. You won&#39;t write production code, but will be responsible for leading technical engagement direction alongside Forward Deployed Engineers.</li>\n<li>Have experience delivering complex, high-stakes technical projects for enterprise customers, where results depend on close coordination and rapid decision-making, ideally in multiple activities within regulated sectors.</li>\n<li>Have an assertive personality: be comfortable, credible, and able to represent Anthropic to high-level executives in high-stakes environments. Overcome ambiguous contexts and bring structure where there isn&#39;t.</li>\n<li>Have a builder mindset: here to create a function, not occupy it.</li>\n</ul>\n<p>Additional assets:</p>\n<ul>\n<li>Experience in financial services, healthcare, life sciences, or pharmaceutical industries.</li>\n<li>Experience in a deployed engineering firm or professional services and consulting firms.</li>\n<li>Exceptional understanding of LLM capabilities and limitations.</li>\n<li>Experience with regulated industries and compliance requirements.</li>\n<li>Experience managing delivery teams with integrated engineers on customer sites.</li>\n<li>Familiarity with AI agent frameworks, usage tool models, and orchestration architectures.</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_d4705425-01c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5153761008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI","ML","LLM","Technical Leadership","Customer Engagement Management","Technical Program Management","Technical Product Management","Startups/Founders","Professional Services","Consulting","Enterprise Software","Architecture Conversations","Technical Trade-Offs","Decision-Making","Complex Project Delivery","High-Stakes Environments","Regulated Sectors","Assertive Personality","Credibility","Representation","Builder Mindset"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:58:58.214Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris, France"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI, ML, LLM, Technical Leadership, Customer Engagement Management, Technical Program Management, Technical Product Management, Startups/Founders, Professional Services, Consulting, Enterprise Software, Architecture Conversations, Technical Trade-Offs, Decision-Making, Complex Project Delivery, High-Stakes Environments, Regulated Sectors, Assertive Personality, Credibility, Representation, Builder Mindset"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f931591c-87a"},"title":"Research Scientist, Frontier Risk Evaluations","description":"<p>As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems.</p>\n<p>For example, you might do any or all of the following:</p>\n<ul>\n<li>Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities;</li>\n</ul>\n<ul>\n<li>Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems;</li>\n</ul>\n<ul>\n<li>Publish evaluation methodologies and write technical reports for policymakers.</li>\n</ul>\n<p>We are seeking talented researchers to join us in shaping this vision.</p>\n<p>Ideally you&#39;d have:</p>\n<ul>\n<li>Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance;</li>\n</ul>\n<ul>\n<li>Practical experience conducting technical research collaboratively. 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The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM&#39;s, as well as evaluation of data quality.</p>\n<p>At Scale, we&#39;re uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale&#39;s ML teams and researchers to build the foundation platform that supports all our ML research and development. 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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&#39;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>Please note that our policy requires a 90-day waiting period before reconsidering candidates for the same role. 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Applications will be reviewed on a rolling basis.</p>\n<p>The annual compensation range for this role is listed below.</p>\n<p>For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</p>\n<p>Annual Salary: $240,000-$315,000 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_cec208e5-844","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5065835008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$240,000-$315,000 USD","x-skills-required":["Technical customer-facing roles","Enterprise customers","Complex buying cycles","Technical communication skills","Scalable cloud architectures","Python","LLM frameworks and tools","Machine learning or data science"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:58:42.551Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Technical customer-facing roles, Enterprise customers, Complex buying cycles, Technical communication skills, Scalable cloud architectures, Python, LLM frameworks and tools, Machine learning or data science","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":240000,"maxValue":315000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_273f3f27-7de"},"title":"Staff Product Manager, Content Experience","description":"<p>We&#39;re looking for a Product Manager to lead our Content Experience strategy. In this role, you will own how users discover, learn from, and act on content: across documentation, in-product help, AI-assisted guidance, and beyond.</p>\n<p>You&#39;ll help define the future of content at Databricks by making it a first-class product experience and integrating content development into product development.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Owning the content experience end-to-end, ensuring it&#39;s helpful, intuitive, and actionable</li>\n<li>Driving strategic improvements to content tooling and workflows</li>\n<li>Building an architecture of participation that enables context experts to contribute directly to content</li>\n<li>Integrating AI to transform content experiences</li>\n<li>Defining metrics that matter and tracking content engagement, time-to-task, support deflection, and user satisfaction</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>7+ years of product management experience, with a proven track record of leading cross-functional initiatives and delivering high-impact user experiences</li>\n<li>Deep understanding of developer tools, data platforms, or technical products with large surface areas</li>\n<li>Strong systems mindset, comfortable designing scalable workflows, content architectures, and tooling integrations</li>\n<li>Experience with developer documentation, content platforms, or product onboarding is a plus</li>\n<li>Strong customer empathy and an obsession with helping users succeed</li>\n<li>Familiarity with AI technologies (especially LLMs) and how they can be applied to content workflows and user guidance</li>\n<li>Experience working with technical and non-technical contributors in a collaborative content ecosystem</li>\n</ul>\n<p>Pay Range Transparency: Databricks is committed to fair and equitable compensation practices. The pay range for this role is $181,700-$249,800 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_273f3f27-7de","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/8040989002","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$181,700-$249,800 USD","x-skills-required":["Product Management","Content Strategy","AI Technologies","Developer Tools","Data Platforms","Technical Products"],"x-skills-preferred":["LLMs","Content Platforms","Product Onboarding"],"datePosted":"2026-04-18T15:58:39.949Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, California"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Product Management, Content Strategy, AI Technologies, Developer Tools, Data Platforms, Technical Products, LLMs, Content Platforms, Product Onboarding","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":181700,"maxValue":249800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_19fc414d-dcc"},"title":"Specialist Solutions Architect - AI & ML (Communications, Media, Entertainment & Games)","description":"<p>As a Specialist Solutions Architect - AI &amp; 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AI offerings</li>\n</ul>\n<p>What we look for:</p>\n<ul>\n<li>5+ years of hands-on industry ML experience in at least one of the following:</li>\n</ul>\n<ul>\n<li>ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.</li>\n</ul>\n<ul>\n<li>AI Engineer: Experience with the latest techniques in LLMs &amp; agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI</li>\n</ul>\n<ul>\n<li>Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience</li>\n</ul>\n<ul>\n<li>Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike</li>\n</ul>\n<ul>\n<li>Passion for collaboration, life-long learning, and driving business value through ML &amp; AI</li>\n</ul>\n<ul>\n<li>[Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role</li>\n</ul>\n<ul>\n<li>Can meet expectations for technical training and role-specific outcomes within 3 months of hire</li>\n</ul>\n<ul>\n<li>This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed</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 utilising the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. 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Additionally, this role may be eligible for additional benefits such as a commuter stipend.</p>\n<p><strong>About Us</strong></p>\n<p>At Scale, our mission is to develop reliable AI systems for the world&#39;s most important decisions. 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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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.</p>\n<p>You’ll also receive benefits including comprehensive health, dental, and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. 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As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems, intelligent advertising systems, and large-scale machine learning pipelines.</p>\n<p>Our team works on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You&#39;ll work on complex, real-world ML problems at massive scale, and contribute to technical strategy, architecture, and long-term ML roadmap.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design, build, and deploy production-grade machine learning models and systems at scale</li>\n<li>Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring</li>\n<li>Build scalable data and model pipelines with strong reliability, observability, and automated retraining</li>\n<li>Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems</li>\n<li>Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions</li>\n<li>Improve system performance across latency, throughput, and model quality metrics</li>\n<li>Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph &amp; transformers based, and LLM evaluation/alignment</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>3-5+ years of experience building, deploying, and operating machine learning systems in production</li>\n<li>Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals</li>\n<li>ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)</li>\n<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>\n<li>Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure</li>\n<li>Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions</li>\n<li>Experience improving measurable metrics through applied machine learning</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems</li>\n<li>Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)</li>\n<li>Experience working with real-time systems and low-latency production environments</li>\n<li>Background in feature engineering, model optimization, and production monitoring</li>\n<li>Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale</li>\n<li>Advanced degree in Computer Science, Machine Learning, or related quantitative field</li>\n</ul>\n<p>Potential Teams:</p>\n<ul>\n<li>Ads Measurement Modeling</li>\n<li>Ads Targeting and Retrieval</li>\n<li>Advertiser Optimization</li>\n<li>Ads Marketplace Quality</li>\n<li>Ads Creative Effectiveness</li>\n<li>Ads Foundational Representations</li>\n<li>Ads Content Understanding</li>\n<li>Ads Ranking</li>\n<li>Feed Relevance</li>\n<li>Search and Answers Relevance</li>\n<li>ML Understanding</li>\n<li>Notifications Relevance</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive Healthcare Benefits and Income Replacement Programs</li>\n<li>401k with Employer Match</li>\n<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>\n<li>Family Planning Support</li>\n<li>Gender-Affirming Care</li>\n<li>Mental Health &amp; Coaching Benefits</li>\n<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>\n<li>Generous Paid Parental Leave</li>\n</ul>\n<p>Pay Transparency:</p>\n<p>This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.</p>\n<p>To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.</p>\n<p>The base salary range for this position is: $185,800-$260,100 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_467be5c4-940","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/7131932","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$185,800-$260,100 USD","x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs","Spark","Kafka","Ray","Airflow","BigQuery","Redis"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments","Feature engineering","Model optimization","Production monitoring","LLM/Gen AI techniques"],"datePosted":"2026-04-18T15:57:49.850Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments, Feature engineering, Model optimization, Production monitoring, LLM/Gen AI techniques","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":185800,"maxValue":260100,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_439653eb-aeb"},"title":"Product Support Specialist","description":"<p>YOU WILL be at the front lines of safely delivering AI to the world by responding to, investigating, and tracking user needs in your day-to-day. Additionally, you will help us identify – and close – gaps in our team&#39;s technical knowledge, provide high-touch support to strategic customers, and demonstrate deep care for how we systematically support customers at scale.</p>\n<p>Responsibilities:</p>\n<p>Become an expert in all Anthropic products Respond to user support cases with a variety of complexity, from questions for individuals to complex API debugging for large businesses Clearly and empathetically communicate with a wide range of user personas, context-switching between guiding executives in a high-touch model to assisting consumer users in a rapid pace Manage on-call tasks for high-urgency user issues with extreme ownership Prioritize critically and comfortably adapt to an ever-evolving product landscape Operate in ambiguity, making informed decisions even in never-before-seen situations Partner with engineers, teammates, and other internal stakeholders to diagnose and resolve user issues, both individually and at scale Suggest and drive improvements to increase user satisfaction through support processes as well as own initiatives that increase efficiency and drive down contact rates Uplevel our team&#39;s technical knowledge by scoping gaps, working with cross-functional partners to deeply understand relevant nuances, and building resources that grow with our products</p>\n<p>You may be a good fit if you: Have experience in technical product support, including API debugging, preferably in a second tier, escalated, or priority support team Are familiar with APIs and technical SaaS products and can deeply understand technical docs with ease Have demonstrated an ability to thrive in fast-paced, reactive situations while meeting core support metrics targets (e.g. CSAT, SLA, etc.) Possess strong user empathy and are expert in the lifecycle of a support case; you can read between the lines of a user&#39;s question, put yourself in their shoes, and get at the heart of their needs for a speedy, satisfying resolution Have crisp but kind written communication skills and a deep care for the details Enjoy helping others learn about new features and complex concepts Experience troubleshooting SSO, SAML, and OAuth authentication flows Are persistent and curious; you delight in the hunt of tracking down a bug or issue, and are energized by fixing this for all similar users going forward Have experience contributing to the foundations of a support team – this is essential, highly valuable, but often unglamorous work Are proficient at working in a technical environment and are interested in Anthropic&#39;s products Possess a deep sense of ownership, and are excited to help us build our team!</p>\n<p>Strong candidates may also have: Comfort with command line interfaces and basic scripting (Bash, Python, JavaScript) Understanding of LLM capabilities, practical applications, and current limitations Familiarity with enterprise networking concepts and IT infrastructure Familiarity with Git workflows and version control concepts SQL proficiency for querying logs and investigating issues Experience supporting government or public sector customers, including familiarity with compliance requirements and security frameworks Background in team lead roles or managing contract/vendor support teams</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_439653eb-aeb","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4979585008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$116,480-$165,000 USD","x-skills-required":["API debugging","Technical SaaS products","Technical documentation","User empathy","Written communication","Troubleshooting","Command line interfaces","Basic scripting","LLM capabilities","Enterprise networking","Git workflows","SQL","Government or public sector customers"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:57:49.065Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"API debugging, Technical SaaS products, Technical documentation, User empathy, Written communication, Troubleshooting, Command line interfaces, Basic scripting, LLM capabilities, Enterprise networking, Git workflows, SQL, Government or public sector customers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":116480,"maxValue":165000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5dc6e17e-94f"},"title":"Staff Machine Learning Engineer - Community Support Engineering","description":"<p>We&#39;re looking for a Staff Machine Learning Engineer to join our Community Support Engineering team. 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You will be responsible for envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.</p>\n<p>Requirements:</p>\n<ul>\n<li>PhD/Master&#39;s degree in Computer Science or equivalent experience</li>\n<li>6/9+ years of ML engineering experience with ownership responsibility over large-scale software systems</li>\n<li>Background in the design and development of AI and ML systems and services</li>\n<li>Experience with LLM driven chatbot and Agentic AI products is a plus</li>\n<li>Excellent communication skills and the ability to work well within a team and with teams across the engineering, product &amp; design organizations</li>\n</ul>\n<p>Our Commitment to Inclusion &amp; Belonging:</p>\n<p>Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services, and solutions. All qualified individuals are encouraged to apply.</p>\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_5dc6e17e-94f","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/7116975","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$204,000-$255,000 USD","x-skills-required":["PhD/Master's degree in Computer Science or equivalent experience","6/9+ years of ML engineering experience with ownership responsibility over large-scale software systems","Background in the design and development of AI and ML systems and services","Experience with LLM driven chatbot and Agentic AI products","Excellent communication skills and the ability to work well within a team and with teams across the engineering, product & design organizations"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:57:42.346Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - USA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"PhD/Master's degree in Computer Science or equivalent experience, 6/9+ years of ML engineering experience with ownership responsibility over large-scale software systems, Background in the design and development of AI and ML systems and services, Experience with LLM driven chatbot and Agentic AI products, Excellent communication skills and the ability to work well within a team and with teams across the engineering, product & design organizations","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_f1950023-ef7"},"title":"Senior Engineering Manager, Activation","description":"<p>Why join us</p>\n<p>Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly.</p>\n<p>Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world&#39;s best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek.</p>\n<p>Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career.</p>\n<p>Engineering</p>\n<p>Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level , from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.</p>\n<p>What you’ll do</p>\n<p>You will lead an engineering group focused on building the systems and product experiences that power customer activation at Brex, including onboarding, account setup, verifications, integrations, and implementation workflows that help customers realize value quickly. This role requires strategic thinking, operational excellence, technical leadership, and a deep passion for delivering frictionless, AI-enhanced customer journeys.</p>\n<p>The ideal candidate is a seasoned engineering leader with experience scaling user-facing onboarding systems, delivering high-quality product experiences, and partnering deeply across Product, Design, Operations, and GTM teams.</p>\n<p>Where you’ll work</p>\n<p>This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!</p>\n<p>Responsibilities</p>\n<ul>\n<li>Take an active role in driving business and product strategies, championing a seamless, intuitive, and efficient onboarding and implementation experience.</li>\n</ul>\n<ul>\n<li>Collaborate with cross-functional partners across Product, Design, Operations, and Sales to define priorities and deliver delightful customer activation experiences.</li>\n</ul>\n<ul>\n<li>Leverage AI to reimagine and automate onboarding and implementation workflows, improving speed, personalization, and operational leverage.</li>\n</ul>\n<ul>\n<li>Drive execution of the Activation roadmap, ensuring timely, high-quality delivery of systems and features that help customers activate and realize value.</li>\n</ul>\n<ul>\n<li>Lead and manage multiple teams of engineers, including hiring, mentoring, performance management, and establishing strong technical direction.</li>\n</ul>\n<ul>\n<li>Build systems that integrate identity verification, KYC and compliance workflows, customer data ingestion, and implementation tooling in a scalable and reliable manner.</li>\n</ul>\n<ul>\n<li>Drive continuous improvement in engineering processes, technical architecture, and product quality.</li>\n</ul>\n<ul>\n<li>Foster a culture of innovation, collaboration, accountability, and customer obsession across the team.</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</ul>\n<ul>\n<li>Strong technical background and understanding of software development principles.</li>\n</ul>\n<ul>\n<li>Expertise leading full-stack engineering teams delivering end-to-end product experiences.</li>\n</ul>\n<ul>\n<li>Demonstrated track record of shipping customer-facing features across multiple release cycles.</li>\n</ul>\n<ul>\n<li>3+ years of experience managing or leading multiple technical teams in a high-growth environment.</li>\n</ul>\n<ul>\n<li>Regularly works with cross-functional partners (e.g. Product, Design, Operations, Sales) and excels in driving alignment across stakeholders.</li>\n</ul>\n<ul>\n<li>Experience building systems related to onboarding, implementation, identity, workflow automation, customer lifecycle products, or other customer facing experiences.</li>\n</ul>\n<ul>\n<li>Data-driven mindset with the ability to evaluate impact, measure funnel performance, and optimize activation metrics.</li>\n</ul>\n<ul>\n<li>Track record building AI-powered product experiences, including LLM-driven automation and personalization.</li>\n</ul>\n<p>Bonus points</p>\n<ul>\n<li>Experience with data platforms such as Snowflake, Hex, or similar.</li>\n</ul>\n<ul>\n<li>You have started your own technology venture or were an early technical founder/employee. We value entrepreneurial spirit &amp; scrappiness!</li>\n</ul>\n<ul>\n<li>You are a champion for the customer and constantly put yourself in their shoes to create intuitive, frictionless experiences.</li>\n</ul>\n<p>Compensation</p>\n<p>The expected salary range for this role is $300,000 - $375,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.</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_f1950023-ef7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Brex","sameAs":"https://brex.com/","logo":"https://logos.yubhub.co/brex.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/brex/jobs/8330492002","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000 - $375,000","x-skills-required":["Technical leadership","Software development principles","Full-stack engineering","Customer-facing features","Data-driven mindset","AI-powered product experiences","LLM-driven automation","Personalization"],"x-skills-preferred":["Data platforms","Snowflake","Hex","Entrepreneurial spirit","Scrappiness","Customer obsession"],"datePosted":"2026-04-18T15:57:39.757Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, New York, United States"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Technical leadership, Software development principles, Full-stack engineering, Customer-facing features, Data-driven mindset, AI-powered product experiences, LLM-driven automation, Personalization, Data platforms, Snowflake, Hex, Entrepreneurial spirit, Scrappiness, Customer obsession","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":375000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ef18c75a-f72"},"title":"Solutions Architect, Applied AI (Commercial)","description":"<p>As a Solutions Architect, Applied AI (Commercial), you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping customers understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack.\\n\\nYou&#39;ll combine your technical depth with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.\\n\\nAs a Commercial Solutions Architect, you&#39;ll go deep with priority accounts as a hands-on builder, while creating reusable blueprints, demos, and enablement that extend Claude&#39;s reach across the broader Commercial book of business.\\n\\nWorking closely with our Sales, Product, and Engineering teams, you&#39;ll guide customers from initial technical discovery through successful deployment. You&#39;ll leverage your expertise to help customers understand Claude&#39;s capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.\\n\\nResponsibilities:\\n\\n<em> Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation\\n\\n</em> Serve as the primary technical advisor to customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success\\n\\n<em> Support customers building with the Claude API, Claude Code, and Claude for Enterprise\\n\\n</em> Ship working code. Build prototypes and proof-of-concepts hands-on, develop eval frameworks, and write near-production examples that customers can extend\\n\\n<em> Build reusable blueprints, demos, and enablement assets that scale across customers\\n\\n</em> Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack\\n\\n<em> Help customers develop evaluation frameworks to measure Claude&#39;s performance for their specific use cases\\n\\n</em> Identify common integration patterns and contribute insights back to our Product and Engineering teams\\n\\n<em> Travel occasionally to customer sites for workshops, technical deep dives, and relationship building\\n\\n</em> Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns\\n\\nYou may be a good fit if you have:\\n\\n<em> 3+ years of highly technical experience as a software engineer (or equivalent) with some customer-facing exposure, OR 3+ years as a Solutions Architect, Sales Engineer, or Technical Account Manager with strong hands-on building experience\\n\\n</em> A builder identity. You&#39;ve shipped real software, you have technical taste, and you care about the craft of what you build\\n\\n<em> A systems mindset. When you see a problem, your instinct is to ask &quot;how do I make this reusable.&quot; You&#39;d rather build one thing that serves ten customers than ten things that serve one each\\n\\n</em> Strong coding ability. You ship prototypes regularly and can work in a real codebase, not just notebooks. Comfort with Python expected\\n\\n<em> Strong ability to build trust with technical stakeholders and adjust your communication for varied audiences\\n\\n</em> Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders\\n\\n<em> Experience designing scalable cloud architectures and integrating with enterprise systems\\n\\n</em> Familiarity with common LLM frameworks and tools, or a background in machine learning or data science\\n\\n<em> Comfort operating in early-stage, ambiguous environments where the playbook doesn&#39;t exist yet, and a track record of building structure as you go\\n\\n</em> Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities\\n\\n<em> A love of teaching, mentoring, and helping others succeed\\n\\n</em> Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $240,000-$315,000 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_ef18c75a-f72","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5192805008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$240,000-$315,000 USD","x-skills-required":["Python","LLM frameworks","Machine learning","Data science","Cloud architectures","Enterprise systems","Technical communication","Customer-facing skills","Technical depth"],"x-skills-preferred":["Sales engineering","Technical account management","Scalable cloud architectures","Integration with enterprise systems","Common LLM frameworks and tools"],"datePosted":"2026-04-18T15:57:36.898Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, LLM frameworks, Machine learning, Data science, Cloud architectures, Enterprise systems, Technical communication, Customer-facing skills, Technical depth, Sales engineering, Technical account management, Scalable cloud architectures, Integration with enterprise systems, Common LLM frameworks and tools","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":240000,"maxValue":315000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_193a44d6-056"},"title":"Staff Full-Stack Software Engineer, (Forward Deployed), GPS","description":"<p>We&#39;re seeking a Full Stack Software Engineer to join our Global Public Sector team. As a key member of our team, you&#39;ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens.</p>\n<p>You will:</p>\n<ul>\n<li>Serve as the lead technical strategist for public sector engagements, converting ambiguous mission requirements into robust architectural roadmaps and guiding onsite implementation</li>\n<li>Architect the fundamental frameworks for production-grade AI applications, setting the gold standard for how interactive UIs, backend systems, and AI models are integrated at scale to deliver reliable outcomes</li>\n<li>Guide the evolution of cloud infrastructure, ensuring security, global scalability, and long-term system integrity across all environments</li>\n<li>Direct the development of core platforms and shared services, ensuring they solve cross-cutting needs for diverse global client use cases</li>\n<li>Partner with cross-functional leadership to steer the technical roadmap, mentoring senior and junior staff and ensuring all products align with a cohesive, future-proof technical architecture</li>\n<li>Bridge the gap between the field and the core platform by turning real-world client lessons into the reusable patterns that power the entire engineering team</li>\n</ul>\n<p>Ideally you&#39;d have:</p>\n<ul>\n<li>Masters or Phd in Computer Science or equivalent deep industry experience in architecting complex, distributed systems</li>\n<li>10+ years of full-stack expertise across Python, Node.js, and React, with a proven track record of designing high-scale architectures on Kubernetes and global cloud infrastructures (AWS/Azure/GCP)</li>\n<li>Expert ability to design and oversee production-grade ecosystems, ensuring world-class standards for system integrity, security, and long-term scalability</li>\n<li>Extensive experience deploying and troubleshooting sophisticated end-to-end solutions directly within complex, high-security client environments</li>\n<li>A self-driven leader capable of resolving extreme ambiguity, mentoring senior staff, and setting the technical vision for the organization</li>\n<li>A driver of asynchronous workflows and documentation-first cultures to streamline global engineering velocity and reduce friction</li>\n<li>Proficient in Arabic</li>\n</ul>\n<p>Nice to haves:</p>\n<ul>\n<li>Past experience working at a startup as a CTO or founding engineer or in a forward deployed engineer / dedicated customer engineer role</li>\n<li>Experience working cross functionally with operations</li>\n<li>Proven track record of building LLM-driven solutions with the strategic foresight to anticipate landscape shifts and architect future-proof systems.</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_193a44d6-056","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4676610005","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","Node.js","React","Kubernetes","Cloud infrastructure","AI","Machine learning","Distributed systems","Cloud computing","Security"],"x-skills-preferred":["Arabic","LLM-driven solutions","Startup experience","CTO or founding engineer experience","Cross-functional experience with operations"],"datePosted":"2026-04-18T15:57:36.893Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Node.js, React, Kubernetes, Cloud infrastructure, AI, Machine learning, Distributed systems, Cloud computing, Security, Arabic, LLM-driven solutions, Startup experience, CTO or founding engineer experience, Cross-functional experience with operations"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8871a994-591"},"title":"Machine Learning Engineer, Core Engineering","description":"<p>We&#39;re seeking a talented Machine Learning Engineer to join our Core Engineering team. As a Machine Learning Engineer at Pinterest, you will build cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest. You will partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces, while gaining knowledge of how ML works in different areas.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Build cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest</li>\n<li>Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas</li>\n<li>Use data-driven methods and leverage the unique properties of our data to improve candidate retrieval</li>\n<li>Work in a high-impact environment with quick experimentation and product launches</li>\n<li>Keep 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 (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)</li>\n<li>End-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)</li>\n<li>Degree in computer science, machine learning, statistics, or related field</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</ul>\n<p>Relocation Statement:</p>\n<p>This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.</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_8871a994-591","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/6121450","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$138,905-$285,982 USD","x-skills-required":["machine learning","deep learning","data processing pipelines","large-scale machine learning systems","big data technologies","Hadoop","Spark","natural language processing","reinforcement learning","graph representation learning"],"x-skills-preferred":["Cursor","Copilot","Codex","LLM-powered productivity tools","scalable real-time systems","stream data"],"datePosted":"2026-04-18T15:57:30.186Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, data processing pipelines, large-scale machine learning systems, big data technologies, Hadoop, Spark, natural language processing, reinforcement learning, graph representation learning, Cursor, Copilot, Codex, LLM-powered productivity tools, scalable real-time systems, stream data","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":138905,"maxValue":285982,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_95c49f85-a98"},"title":"Staff+ Software Engineer, Observability","description":"<p><strong>About the Role</strong></p>\n<p>Anthropic is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. The Observability team owns the monitoring and telemetry infrastructure that every engineer and researcher at Anthropic depends on,from metrics and logging pipelines to distributed tracing, error analytics, alerting, and the dashboards and query interfaces that make it all actionable.</p>\n<p>As Anthropic scales its infrastructure across massive GPU, TPU, and Trainium clusters, the volume and complexity of operational data is growing by orders of magnitude. We’re building next-generation observability systems,high-throughput ingest pipelines, cost-efficient columnar storage, unified query layers across signals, and agentic diagnostic tools,to ensure that engineers can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become exponentially more complex.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design and build scalable telemetry ingest and storage pipelines for metrics, logs, traces, and error data across Anthropic’s multi-cluster infrastructure</li>\n</ul>\n<ul>\n<li>Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organisational growth</li>\n</ul>\n<ul>\n<li>Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services</li>\n</ul>\n<ul>\n<li>Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliability targets with minimal noise</li>\n</ul>\n<ul>\n<li>Reduce mean time to detection and resolution by building cross-signal correlation, unified query interfaces, and AI-assisted diagnostic tooling</li>\n</ul>\n<ul>\n<li>Partner with Research, Inference, Product, and Infrastructure teams to ensure observability solutions meet the unique needs of each organisation</li>\n</ul>\n<p><strong>You May Be a Good Fit If You</strong></p>\n<ul>\n<li>Have 10+ years of relevant industry experience building and operating large-scale observability or monitoring infrastructure</li>\n</ul>\n<ul>\n<li>Have deep experience with at least one observability signal area (metrics, logging, tracing, or error analytics) and familiarity with the others</li>\n</ul>\n<ul>\n<li>Understand high-throughput data pipelines, columnar storage engines, and the tradeoffs involved in ingesting and querying telemetry data at scale</li>\n</ul>\n<ul>\n<li>Have experience operating or building on top of observability platforms such as Prometheus, Grafana, ClickHouse, OpenTelemetry, or similar systems</li>\n</ul>\n<ul>\n<li>Have strong proficiency in at least one of Python, Rust, or Go</li>\n</ul>\n<ul>\n<li>Have excellent communication skills and enjoy partnering with internal teams to improve their operational visibility and incident response capabilities</li>\n</ul>\n<ul>\n<li>Are excited about building foundational infrastructure and are comfortable working independently on ambiguous, high-impact technical challenges</li>\n</ul>\n<p><strong>Strong Candidates May Also Have</strong></p>\n<ul>\n<li>Experience operating metrics systems at very high cardinality (hundreds of millions of active time series or more)</li>\n</ul>\n<ul>\n<li>Experience with log storage migrations or operating columnar databases (ClickHouse, BigQuery, or similar) for analytics workloads</li>\n</ul>\n<ul>\n<li>Experience with OpenTelemetry instrumentation, collector pipelines, and tail-based sampling strategies</li>\n</ul>\n<ul>\n<li>Experience building or operating alerting platforms, on-call tooling, or SLO frameworks at scale</li>\n</ul>\n<ul>\n<li>Experience with Kubernetes-native monitoring, eBPF-based observability, or continuous profiling</li>\n</ul>\n<ul>\n<li>Interest in applying AI/LLMs to operational workflows such as automated root cause analysis, anomaly detection, or intelligent alerting</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n</ul>\n<ul>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n</ul>\n<ul>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<ul>\n<li>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.</li>\n</ul>\n<ul>\n<li>Visa sponsorship: We do sponsor visas! However, we aren’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.</li>\n</ul>\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’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><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.</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_95c49f85-a98","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5102440008","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"£325,000-£390,000 GBP","x-skills-required":["observability","telemetry","metrics","logging","tracing","error analytics","alerting","SLO infrastructure","cross-signal correlation","unified query interfaces","AI-assisted diagnostic tooling","Python","Rust","Go","Prometheus","Grafana","ClickHouse","OpenTelemetry"],"x-skills-preferred":["high-throughput data pipelines","columnar storage engines","Kubernetes-native monitoring","eBPF-based observability","continuous profiling","AI/LLMs","automated root cause analysis","anomaly detection","intelligent alerting"],"datePosted":"2026-04-18T15:57:27.177Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"observability, telemetry, metrics, logging, tracing, error analytics, alerting, SLO infrastructure, cross-signal correlation, unified query interfaces, AI-assisted diagnostic tooling, Python, Rust, Go, Prometheus, Grafana, ClickHouse, OpenTelemetry, high-throughput data pipelines, columnar storage engines, Kubernetes-native monitoring, eBPF-based observability, continuous profiling, AI/LLMs, automated root cause analysis, anomaly detection, intelligent alerting","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":325000,"maxValue":390000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_13a80645-7e0"},"title":"Technical Deployment Lead, Applied AI","description":"<p>As a Technical Deployment Lead on the Claude Agentic Solutions team, you will lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries.</p>\n<p>You&#39;ll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes. This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion.</p>\n<p>You will champion our mission in the field, ensure world-class delivery, and bring insights back to our product and research teams on a regular basis. You&#39;ll own engagements end-to-end, from SOW through production deployment.</p>\n<p>You&#39;ll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organisational complexity that comes with deploying AI agents in enterprise environments.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Manage the technical delivery plan for each engagement.</li>\n<li>Structure the SOW by clearly defining the scope, steps, dependencies, success criteria, and value hypotheses.</li>\n<li>Translate customer commercial objectives into a sequenced roadmap that our FDEs execute.</li>\n<li>Supervise technical discovery: map customer workflows, identify constraints, define the MVP scope, and shape the solution architecture for custom agent deployments.</li>\n<li>Lead the execution and delivery of daily engineering work within Anthropic and customer teams. Ensure project progress is smooth and sequenced. Make real-time trade-offs on scope and priority to preserve the critical path.</li>\n<li>Ensure product scope for field missions: define the MVP, write requirements documentation, prioritise the engineering backlog, and manage scope against success criteria as requirements evolve. Own the customer relationship throughout delivery. Organise executive briefings, manage communications with stakeholders regarding technical leads and supply, and represent Anthropic remote to senior commercial and technical executives in terms of technical credibility.</li>\n<li>Master value measurement and ROI: define impact hypotheses, establish baselines, and key performance indicators, conduct pre- and post-deployment measurements, and communicate results to executive sponsors.</li>\n<li>BOYD reusable solution patterns, evaluation frameworks, and technical manuals. Record best practices from various interactions and transmit signals from the field to Product and Research teams to improve our platform and models.</li>\n</ul>\n<p>Navigating enterprise and regulatory complexity: security audits, legal approvals, procurement processes, compliance requirements, and organisational dynamics.</p>\n<p>Manage scope and change: manage evolving requirements, define expectations, negotiate contract modifications, identify risks upfront, and signal them with clear context, when necessary.</p>\n<p>Manage delivery operations: sprint ceremonies, step reviews, and progress reports.</p>\n<p>Visit customer sites to build relationships, unlock deliveries, and accelerate adoption (target 25-50%).</p>\n<p>Profile:</p>\n<ul>\n<li>More than 5 years of technical leadership experience with customers. This can include technical engagement management, technical program management, or technical product management, founders/startups, technical profiles, professional services, consulting, or enterprise software.</li>\n<li>Have deployed AI-based agent solutions, ML, or LLM. You understand applicable models, integration approaches, and reality on the ground.</li>\n<li>Can hold architecture conversations with engineering stakeholders, evaluate technical trade-offs, and test technical decisions under pressure. You won&#39;t write production code, but will be responsible for leading technical direction of engagements alongside Forward Deployed Engineers.</li>\n<li>Have experience delivering complex, high-stakes technical projects for enterprise customers, whose results depend on close coordination and rapid decision-making, ideally in multiple activities within regulated sectors.</li>\n<li>Have an assertive personality: you&#39;re comfortable, credible, and able to represent Anthropic in high-stakes environments.</li>\n<li>Overcome ambiguous contexts and bring structure where there isn&#39;t.</li>\n<li>Have a builder mindset: you&#39;re here to create a function, not occupy it.</li>\n</ul>\n<p>Additional assets:</p>\n<ul>\n<li>Experience in financial services, healthcare, life sciences, or pharmaceutical industries.</li>\n<li>Experience in a field-deployed engineering organisation or professional services and consulting firms.</li>\n<li>Exceptional understanding of LLM capabilities and limitations.</li>\n<li>Experience with regulated industries and compliance requirements.</li>\n<li>Experience managing delivery teams with integrated engineers on customer sites.</li>\n<li>Familiarity with AI agent frameworks, usage tool models, and orchestration architectures.</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_13a80645-7e0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5153761008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI","Machine Learning","LLM","Technical Leadership","Project Management","Customer Relationship Management","Value Measurement","ROI","Solution Architecture","Technical Discovery","Engineering Work Management","Product Scoping","Stakeholder Management","Organisational Complexity","Regulatory Compliance","Security Audits","Legal Approvals","Procurement Processes","Compliance Requirements","Enterprise Software","Professional Services","Consulting","Founders/Startups","Technical Profiles"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:57:10.848Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris, France"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI, Machine Learning, LLM, Technical Leadership, Project Management, Customer Relationship Management, Value Measurement, ROI, Solution Architecture, Technical Discovery, Engineering Work Management, Product Scoping, Stakeholder Management, Organisational Complexity, Regulatory Compliance, Security Audits, Legal Approvals, Procurement Processes, Compliance Requirements, Enterprise Software, Professional Services, Consulting, Founders/Startups, Technical Profiles"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_13505dca-891"},"title":"Solutions Architect, Applied AI (Commercial)","description":"<p>As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping customers understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack.\\n\\nYou&#39;ll combine your technical depth with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.\\n\\nAs a Commercial Solutions Architect, you&#39;ll go deep with priority accounts as a hands-on builder, while creating reusable blueprints, demos, and enablement that extend Claude&#39;s reach across the broader Commercial book of business.\\n\\nWorking closely with our Sales, Product, and Engineering teams, you&#39;ll guide customers from initial technical discovery through successful deployment. You&#39;ll leverage your expertise to help customers understand Claude&#39;s capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.\\n\\nResponsibilities:\\n\\nPartner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation\\n\\nServe as the primary technical advisor to customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success\\n\\nSupport customers building with the Claude API, Claude Code, and Claude for Enterprise\\n\\nShip working code. Build prototypes and proof-of-concepts hands-on, develop eval frameworks, and write near-production examples that customers can extend\\n\\nBuild reusable blueprints, demos, and enablement assets that scale across customers\\n\\nGuide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack\\n\\nHelp customers develop evaluation frameworks to measure Claude&#39;s performance for their specific use cases\\n\\nIdentify common integration patterns and contribute insights back to our Product and Engineering teams\\n\\nTravel occasionally to customer sites for workshops, technical deep dives, and relationship building\\n\\nMaintain strong knowledge of the latest developments in LLM capabilities and implementation patterns\\n\\nYou may be a good fit if you have:\\n\\n3+ years of highly technical experience as a software engineer (or equivalent) with some customer-facing exposure, OR 3+ years as a Solutions Architect, Sales Engineer, or Technical Account Manager with strong hands-on building experience\\n\\nA builder identity. You&#39;ve shipped real software, you have technical taste, and you care about the craft of what you build\\n\\nA systems mindset. When you see a problem, your instinct is to ask &quot;how do I make this reusable.&quot; You&#39;d rather build one thing that serves ten customers than ten things that serve one each\\n\\nStrong coding ability. You ship prototypes regularly and can work in a real codebase, not just notebooks. Comfort with Python expected\\n\\nStrong ability to build trust with technical stakeholders and adjust your communication for varied audiences\\n\\nStrong technical communication skills with the ability to translate customer requirements between technical and business stakeholders\\n\\nExperience designing scalable cloud architectures and integrating with enterprise systems\\n\\nFamiliarity with common LLM frameworks and tools, or a background in machine learning or data science\\n\\nComfort operating in early-stage, ambiguous environments where the playbook doesn&#39;t exist yet, and a track record of building structure as you go\\n\\nExcitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities\\n\\nA love of teaching, mentoring, and helping others succeed\\n\\nPassion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary:$240,000-$315,000 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_13505dca-891","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5192805008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$240,000-$315,000 USD","x-skills-required":["Python","LLM","Cloud Architecture","Enterprise Integration","Machine Learning","Data Science"],"x-skills-preferred":["Builder Identity","Systems Mindset","Technical Communication","Customer-Facing Skills"],"datePosted":"2026-04-18T15:57:04.205Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, LLM, Cloud Architecture, Enterprise Integration, Machine Learning, Data Science, Builder Identity, Systems Mindset, Technical Communication, Customer-Facing Skills","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":240000,"maxValue":315000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c38cbb6f-4b7"},"title":"Staff Software Engineer, Inference","description":"<p>Job Title: Staff Software Engineer, Inference\\n\\nLocation: Dublin, IE\\n\\nDepartment: Software Engineering - Infrastructure\\n\\nJob Description:\\n\\nAbout Anthropic\\n\\nAnthropic&#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.\\n\\nAbout the role:\\n\\nOur Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry&#39;s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.\\n\\nThe team has a dual mandate: maximizing compute efficiency to serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.\\n\\nAs a Staff Software Engineer on our Inference team, you will work end to end, identifying and addressing key infrastructure blockers to serve Claude to millions of users while enabling breakthrough AI research. Strong candidates should have familiarity with performance optimization, distributed systems, large-scale service orchestration, and intelligent request routing. Familiarity with LLM inference optimization, batching strategies, and multi-accelerator deployments is highly encouraged but not strictly necessary.\\n\\nStrong candidates may also have experience with:\\n\\n- High-performance, large-scale distributed systems\\n\\n- Implementing and deploying machine learning systems at scale\\n\\n- Load balancing, request routing, or traffic management systems\\n\\n- LLM inference optimization, batching, and caching strategies\\n\\n- Kubernetes and cloud infrastructure (AWS, GCP)\\n\\n- Python or Rust\\n\\nYou may be a good fit if you:\\n\\n- Have significant software engineering experience, particularly with distributed systems\\n\\n- Are results-oriented, with a bias towards flexibility and impact\\n\\n- Pick up slack, even if it goes outside your job description\\n\\n- Want to learn more about machine learning systems and infrastructure\\n\\n- Thrive in environments where technical excellence directly drives both business results and research breakthroughs\\n\\n- Care about the societal impacts of your work\\n\\nRepresentative projects across the org:\\n\\n- Designing intelligent routing algorithms that optimize request distribution across thousands of accelerators\\n\\n- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads\\n\\n- Building production-grade deployment pipelines for releasing new models to millions of users\\n\\n- Integrating new AI accelerator platforms to maintain our hardware-agnostic competitive advantage\\n\\n- Contributing to new inference features (e.g., structured sampling, prompt caching)\\n\\n- Supporting inference for new model architectures\\n\\n- Analyzing observability data to tune performance based on real-world production workloads\\n\\n- Managing multi-region deployments and geographic routing for global customers\\n\\nDeadline to apply: None. Applications will be reviewed on a rolling basis.\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary:€295.000-€355.000 EUR\\n\\nLogistics\\n\\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\\n\\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\\n\\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\\n\\nLocation-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.\\n\\nVisa 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.\\n\\nWe 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.\\n\\nYour 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.\\n\\nHow we&#39;re different\\n\\nWe 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.\\n\\nThe 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: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.\\n\\nCome work with us!\\n\\nAnthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates&#39; AI Usage: Learn about our policy for using AI in our application process</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_c38cbb6f-4b7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5150472008","x-work-arrangement":"hybrid","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"€295.000-€355.000 EUR","x-skills-required":["performance optimization","distributed systems","large-scale service orchestration","intelligent request routing","LLM inference optimization","batching strategies","multi-accelerator deployments","Kubernetes","cloud infrastructure","Python","Rust"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:57:00.340Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dublin, IE"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"performance optimization, distributed systems, large-scale service orchestration, intelligent request routing, LLM inference optimization, batching strategies, multi-accelerator deployments, Kubernetes, cloud infrastructure, Python, Rust"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_15bab201-11c"},"title":"Machine Learning Research Engineer, Agent Data Foundation - Enterprise GenAI","description":"<p>We are seeking a Machine Learning Research Engineer to join our Enterprise ML Research Lab. As a key member of our team, you will work on cutting-edge research to define the data flywheel that makes the whole machine move. This includes research around synthetic environments from task definitions, building agents for trace analysis, and contributing to a cutting-edge framework that automatically hill-climbs agent-building from an eval set.</p>\n<p>You will:</p>\n<ul>\n<li>Build synthetic data pipelines to generate enterprise environments to use for RL post-training</li>\n<li>Create agents to convert traces from production into actionable insights to use to improve agents</li>\n<li>Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms</li>\n<li>Train state-of-the-art models, developed both internally and from the community, to deploy to our enterprise customers</li>\n</ul>\n<p>Ideally, you&#39;d have:</p>\n<ul>\n<li>3+ years of building with LLMs in a production environment</li>\n<li>Clear experiences with constructing high-quality data to use to improve an LLM/Agent</li>\n<li>Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years</li>\n<li>PhD or Masters in Computer Science or a related field</li>\n</ul>\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.</p>\n<p>You&#39;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. 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You&#39;ll be responsible for leading &amp; growing the International Partnerships Applied AI team, establishing processes and best practices for partner-led pre-sales engagements, helping each team member achieve success, high productivity, and career growth, and representing Anthropic as a technical lead on some of its most important international partnerships.</p>\n<p>In collaboration with the Sales, Partnerships, Product, and Engineering teams, you&#39;ll help partners incorporate leading-edge AI systems into their practices, solutions, and customer engagements. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike.</p>\n<p>You will play a critical role in identifying opportunities to accelerate indirect revenue, enable partner AI practices, and execute on long-term international GTM strategy, while maintaining our best-in-class safety standards.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Team Leadership &amp; Development: Manage and mentor a team of Applied AI, Partner Solutions Architects, providing both technical guidance and career development. Set goals and reviews for your team, promoting growth and output</li>\n</ul>\n<ul>\n<li>Strategic Technical Partnership: Serve as the senior technical thought partner to the Anthropic international GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities across international markets</li>\n</ul>\n<ul>\n<li>Partner Ecosystem Enablement: Embed your team with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues</li>\n</ul>\n<ul>\n<li>Joint Solution Development: Lead your team in collaborating with partners to identify high-value industry-specific GenAI applications, develop joint solutions, and codify reference architectures / best practices to accelerate time to deployment across international markets</li>\n</ul>\n<ul>\n<li>Customer Deal Support: Own the technical portions of partner-led pre-sales engagements, ensuring your team intervenes directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance</li>\n</ul>\n<ul>\n<li>Partner Ecosystem &amp; Events: Represent Anthropic at international partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions</li>\n</ul>\n<ul>\n<li>Cross-Functional Collaboration: Drive collaboration from cross-functional teams to influence and unify stakeholders at all levels of the organization to drive business outcomes. Partner closely with your aligned GTM leadership to co-build international partner strategies</li>\n</ul>\n<ul>\n<li>Product Feedback: Validate and gather feedback on Anthropic&#39;s products and offerings, especially as they relate to international partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy</li>\n</ul>\n<ul>\n<li>Thought Leadership: Contribute to thought leadership through conference presentations, webinars, and technical content creation focused on the international partner ecosystem</li>\n</ul>\n<p>You may be a good fit if you:</p>\n<ul>\n<li>7+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager</li>\n</ul>\n<ul>\n<li>5+ years of technical go-to-market management experience, specifically managing pre-sales or partner-facing technical teams across EMEA, APAC, and other international regions.</li>\n</ul>\n<ul>\n<li>Track record of successfully building and scaling partnerships with GSIs (e.g., Accenture, Deloitte, WPP, TCS, Infosys) and/or cloud providers (AWS, GCP) to solve complex technical challenges across international markets</li>\n</ul>\n<ul>\n<li>Experience with the unique dynamics of partner-led selling and delivery, including indirect revenue models and partner enablement at scale</li>\n</ul>\n<ul>\n<li>Deep technical proficiency with enterprise AI deployments, API integrations, and production LLM use cases</li>\n</ul>\n<ul>\n<li>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders including C-suite executives, engineering &amp; IT teams, and partner leadership</li>\n</ul>\n<ul>\n<li>Have an organizational mindset and enjoy building foundational teams in a relatively unstructured environment</li>\n</ul>\n<ul>\n<li>Have excellent communication, collaboration, and coaching abilities</li>\n</ul>\n<ul>\n<li>Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments</li>\n</ul>\n<ul>\n<li>Strong executive presence and ability to foster deep relationships with technical leaders and partner engineering teams</li>\n</ul>\n<ul>\n<li>Have at least a high-level familiarity with the architecture and operation of large language models and/or ML in general</li>\n</ul>\n<ul>\n<li>Experience with prompt engineering, LLM evaluation, and architecting AI-powered systems</li>\n</ul>\n<ul>\n<li>A love of teaching, mentoring, and helping others succeed</li>\n</ul>\n<ul>\n<li>Have a passion for making powerful technology safe and societally beneficial</li>\n</ul>\n<ul>\n<li>Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks</li>\n</ul>\n<p>Strong candidates may have:</p>\n<ul>\n<li>Partner SA Leadership at Scale: 5+ years leading partner-facing solution architect teams through hypergrowth, with direct experience managing both senior SAs and developing junior talent in complex partner ecosystem environments</li>\n</ul>\n<ul>\n<li>AI/ML Technical Depth + Executive Engagement: Hands-on experience with AI/ML platforms and enterprise integration patterns, combined with proven track record engaging C-level stakeholders and partner leadership in large-scale technical evaluations and joint GTM motions</li>\n</ul>\n<ul>\n<li>GSI Practice Building: Experience helping GSIs or consultancies build or scale their AI/ML practices, including enablement programs, certification paths, and joint solution development</li>\n</ul>\n<p>Annual compensation range for this role is £170,000-£215,000 GBP.</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_890da396-bd8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5146999008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£170,000-£215,000 GBP","x-skills-required":["Technical customer-facing/partner-facing roles","Solutions Architect","Sales Engineer","Partner Sales Engineer","Technical Account Manager","Technical go-to-market management","Enterprise AI deployments","API integrations","Production LLM use cases","Large language models","ML in general","Prompt engineering","LLM evaluation","Architecting AI-powered systems"],"x-skills-preferred":["Partner SA Leadership at Scale","AI/ML Technical Depth + Executive Engagement","GSI Practice Building"],"datePosted":"2026-04-18T15:56:55.674Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Technical customer-facing/partner-facing roles, Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager, Technical go-to-market management, Enterprise AI deployments, API integrations, Production LLM use cases, Large language models, ML in general, Prompt engineering, LLM evaluation, Architecting AI-powered systems, Partner SA Leadership at Scale, AI/ML Technical Depth + Executive Engagement, GSI Practice Building","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":170000,"maxValue":215000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ac45e205-e7d"},"title":"Engineering Manager, Inference Routing and Performance","description":"<p><strong>About the role\\nEvery request that hits Claude , from claude.ai, the API, our cloud partners, or internal research , passes through a routing decision. Not a generic load balancer round-robin, but a decision that accounts for what&#39;s already cached where, which accelerator the request runs best on, and what else is in flight across the fleet.\\n\\nGet it right and you extract meaningfully more throughput from the same hardware. Get it wrong and you burn capacity, miss latency SLOs, or shed load that shouldn&#39;t have been shed.\\n\\nThe Inference Routing team owns this layer. We build the cluster-level routing and coordination plane for Anthropic&#39;s inference fleet , the system that sits between the API surface and the inference engines themselves, making fleet-wide efficiency decisions in real time.\\n\\nAs Anthropic moves from &quot;many independent inference replicas&quot; toward &quot;a single warehouse-scale computer running a coordinated program,&quot; Dystro is the coordination layer. This is a deeply technical team.\\n\\nThe engineers here design custom load-balancing algorithms, build quantitative models of system performance, debug latency spikes that cross kernel, network, and framework boundaries, and reason carefully about cache placement across thousands of accelerators.\\n\\nThey work shoulder-to-shoulder with teams that write kernels and ML framework internals.\\n\\nThe EM for this team doesn&#39;t need to write kernels , but they do need the systems depth to make architectural calls, evaluate deeply technical candidates, and spot when a proposed optimization will have second-order effects on the fleet.\\n\\nYou&#39;ll inherit a strong team of distributed-systems engineers, and you&#39;ll be accountable for two things that pull in different directions: shipping system-level performance improvements that measurably increase fleet throughput and efficiency, and running the team operationally so that deploys are safe, incidents are rare, and the teams who depend on Dystro can plan around you with confidence.\\n\\nThe job is holding both.\\n\\n## Representative work:\\nThings the Inference Routing EM actually spends time on:\\n- Deciding whether a proposed routing algorithm change is worth the deploy risk, given the modeled throughput gain and the blast radius if it regresses\\n- Sequencing a quarter where KV-cache offload, a new coordination protocol, and two model launches all compete for the same engineers\\n- Working through a persistent tail-latency regression with the team , walking down from fleet-level metrics to per-replica behavior to a root cause in the networking stack\\n- Building the case (with numbers) to peer teams for why a cross-team protocol change unlocks the next efficiency win\\n- Running the post-incident review after a cache-eviction bug caused a capacity event, and turning it into process changes that stick\\n- Interviewing a candidate who has built schedulers at supercomputing scale, and deciding whether they&#39;d be additive to a team that already goes deep\\n\\n## What you&#39;ll do:\\nDrive system-level performance\\n- Own the technical roadmap for cluster-level inference efficiency , routing decisions, cache placement and eviction, cross-replica coordination, and the protocols that keep routing and inference engines in sync\\n- Partner with the inference engine, kernels, and performance teams to identify fleet-level throughput and latency wins, then turn those into shipped improvements with measurable results\\n- Build the team&#39;s habit of quantitative performance modeling: claim a win only when you can measure it, and know before you ship what the expected effect is\\n\\nDeliver reliably and operate cleanly\\n- Set technical strategy for how routing evolves across heterogeneous hardware (GPUs, TPUs, Trainium) and across all our serving surfaces\\n- Run the team&#39;s operational backbone , on-call rotation, incident response, postmortem review, deploy safety , so the team can ship aggressively without the system becoming fragile\\n- Create clarity at a seam: Inference Routing sits between the API surface, the inference engines, and the cloud deployment teams. You&#39;ll make sure commitments are realistic, dependencies are understood, and nobody is surprised\\n\\nBuild and grow the team\\n- Develop and retain a strong existing team, and hire against the bar described above: people who can go to the OS and framework level when the problem demands it, and who care about production reliability\\n- Coach engineers through a roadmap where priorities shift with model launches, new hardware, and scaling demands. We pair a lot here , you&#39;ll help make that collaboration pattern productive\\n- Pick up slack when it matters. This is a small team in a critical path; sometimes the EM is the one unblocking a stuck deploy or synthesizing a design debate\\n\\n## You may be a good fit if you:\\n- Have 5+ years of engineering management experience, ideally with at least part of that leading teams on critical-path production infrastructure at scale\\n- Have a deep systems background , load balancing, scheduling, cache-coherent distributed state, high-performance networking, or similar. You need enough depth to make architectural calls about routing and efficiency, and to evaluate candidates who go to the kernel and framework level\\n- Have shipped performance improvements in large-scale systems and can explain, with numbers, what the impact was\\n- Have run production infrastructure with real operational stakes: on-call, incident response, capacity events, deploy discipline\\n- Are results-oriented with a bias toward impact, and comfortable working in a space where throughput, latency, stability, and feature velocity all pull in different directions\\n- Build strong relationships across team boundaries , this is a seam role, and much of the job is making sure other teams can rely on yours\\n- Are curious about machine learning systems. You don&#39;t need an ML research background, but you should want to learn how transformer inference actually works and how that shapes the systems problems\\n\\nStrong candidates may also have:\\n- Experience with LLM inference serving , KV caching, continuous batching, request scheduling, prefill/decode disaggregation\\n- Background in cluster schedulers, load balancers, service meshes, or coordination planes at scale\\n- Familiarity with heterogeneous accelerator fleets (GPU/TPU/Trainium) and how hardware differences affect workload placement\\n- Experience with GPU/accelerator programming, ML framework internals, or OS-level performance debugging , enough to follow and evaluate the technical work, not necessarily to do it daily\\n- Led teams at supercomputing or hyperscaler infrastructure scale\\n- Led teams through rapid-growth periods where hiring and onboarding competed with roadmap delivery\\n\\nThe annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\nAnnual Salary: $405,000-$485,000 USD</strong></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_ac45e205-e7d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5155391008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$405,000-$485,000 USD","x-skills-required":["engineering management","distributed systems","load balancing","scheduling","cache-coherent distributed state","high-performance networking","machine learning systems"],"x-skills-preferred":["LLM inference serving","cluster schedulers","load balancers","service meshes","coordination planes","heterogeneous accelerator fleets","GPU/TPU/Trainium","GPU/accelerator programming","ML framework internals","OS-level performance debugging"],"datePosted":"2026-04-18T15:56:48.587Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"engineering management, distributed systems, load balancing, scheduling, cache-coherent distributed state, high-performance networking, machine learning systems, LLM inference serving, cluster schedulers, load balancers, service meshes, coordination planes, heterogeneous accelerator fleets, GPU/TPU/Trainium, GPU/accelerator programming, ML framework internals, OS-level performance debugging","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":405000,"maxValue":485000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_25f30c30-4ac"},"title":"Sr. Staff GenAI Content & Conversational Designer, Monetization","description":"<p>We&#39;re seeking a highly adaptable Sr. Staff GenAI Content &amp; Conversational Designer to join our Monetization design team. As a key member of our team, you&#39;ll support projects and teams across the suite of Pinterest business products, ramping up quickly where help is needed most.</p>\n<p>Your primary responsibility will be to lead conversation design and strategy for a multi-agent AI powered Pinterest Business Assistant to help business users (merchants, advertisers, and agencies) create inspired content, connect with customers, and achieve their business goals.</p>\n<p>To succeed in this role, you&#39;ll need to act as the voice of the user by becoming an expert in our business products and leveraging research to inform the design of the AI assistant. You&#39;ll also drive improvements in prompt and skill management, owning the process from conception to production, and rapidly adapting to new technologies.</p>\n<p>In addition to your technical skills, you&#39;ll need to be able to collaborate cross-functionally with researchers, product managers, engineers, and stakeholders to establish conversational, cohesive experiences with a unified voice. You&#39;ll apply systematic thinking to your work, contributing to scalable, consistent design patterns, and participating in critique to strengthen your designs.</p>\n<p>As a Sr. Staff GenAI Content &amp; Conversational Designer, you&#39;ll actively seek learning opportunities to grow your craft, define success metrics for novel AI features, and obsess over building trustworthy, high-impact AI systems.</p>\n<p>We&#39;re looking for someone with a strong background in user-focused product conversation and content design, with experience shaping content for multi-disciplinary projects. You should have experience with LLMs, prompt shaping/engineering and working on AI product flows and with agentic systems. A portfolio demonstrating breadth and creativity and proven experience in content design, design thinking and product strategy is essential.</p>\n<p>This position is not eligible for relocation assistance. You&#39;ll need to be in the office for in-person collaboration 1-2 times/quarter, and therefore can be situated anywhere in the country.</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_25f30c30-4ac","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/7684632","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$146,561-$301,744 USD","x-skills-required":["GenAI","Content Design","Conversational Design","User-Focused Product Conversation","Content Strategy","LLMs","Prompt Shaping/Engineering","AI Product Flows","Agentic Systems"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:56:47.263Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Remote, US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Design","industry":"Technology","skills":"GenAI, Content Design, Conversational Design, User-Focused Product Conversation, Content Strategy, LLMs, Prompt Shaping/Engineering, AI Product Flows, Agentic Systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":146561,"maxValue":301744,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_45cde3e1-29d"},"title":"Applied AI Engineer, Enterprise GenAI","description":"<p>We&#39;re looking for an Applied AI Engineer to join our Enterprise Engineering team. As an Applied AI Engineer, you&#39;ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins.</p>\n<p>Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you&#39;ll use to improve your product&#39;s performance. You&#39;ll own, plan, and optimize the AI behind our Enterprise customer&#39;s deepest technical problems, leveraging our Scale Generative Platform (SGP) to build the most advanced AI agents across the industry.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Own, plan, and optimize the AI behind our Enterprise customer&#39;s deepest technical problems</li>\n<li>Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more</li>\n<li>Have experience gathering business requirements and translating them into technical solutions</li>\n<li>Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs</li>\n<li>Push production code in multiple development environments, writing and debugging code directly in both our customer&#39;s and Scale&#39;s codebases.</li>\n</ul>\n<p>Ideal candidate will have a love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client&#39;s business goals, a strong engineering background, deep familiarity with a data-driven approach when iterating on machine learning models, and experience working with cloud technology stack and developing machine learning models in a cloud environment.</p>\n<p>Nice to have: strong knowledge of software engineering best practices, experience building applications taking advantage of Generative AI in real, production use cases, and familiarity with state of the art LLMs and their strengths/weaknesses.</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_45cde3e1-29d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Scale","sameAs":"https://scale.com/","logo":"https://logos.yubhub.co/scale.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/scaleai/jobs/4514173005","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$216,000-$270,000 USD","x-skills-required":["Python","Machine Learning","Cloud Technology Stack","Data-Driven Approach","Software Engineering Best Practices"],"x-skills-preferred":["Generative AI","State of the Art LLMs","Multimodal Functionality","Tool-Calling"],"datePosted":"2026-04-18T15:56:38.201Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA; New York, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Machine Learning, Cloud Technology Stack, Data-Driven Approach, Software Engineering Best Practices, Generative AI, State of the Art LLMs, Multimodal Functionality, Tool-Calling","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216000,"maxValue":270000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f418117c-d57"},"title":"Director, Engineering - Patient","description":"<p>We are looking for a Director, Engineering - Patient to lead our Patient Core Experience team. As a key member of our engineering leadership team, you will be responsible for setting the technical strategy for our core patient experience, leading three engineering managers, and scaling the org from 18 to 30+ engineers over the next 18 months. You will also co-own patient funnel metrics with your Product and Data counterparts, drive delivery of ML-powered ranking, reimagined patient onboarding, and patient activation systems, and build an engineering culture with clear standards for velocity, quality, and technical excellence.</p>\n<p>Required experience includes 10+ years of software engineering experience, 5+ years managing engineering managers, and leading engineering for a consumer or marketplace product where search, matching, ranking, or personalization was core to the business. You should also have scaled an engineering org through a high-growth phase (25+ to 50+) while maintaining velocity and quality, and be technically strong enough to make sound architecture calls on ranking/ML systems, marketplace infrastructure, and consumer-facing surfaces.</p>\n<p>Nice-to-have experience includes healthcare experience or other regulated industries where data sensitivity and clinical consequences raise the stakes, experience with marketplace dynamics (supply/demand balancing, multi-sided incentive design), experience building LLM-based product features (conversational interfaces, intelligent triage, AI-assisted workflows), and experience rethinking team structure or hiring profiles in response to AI productivity gains.</p>\n<p>Our stack includes Python (Django/FastAPI), TypeScript/React, Elasticsearch, PostgreSQL, Redis, dbt, Snowflake, Temporal, and custom ML models. 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You&#39;ll work across the full sales cycle, from initial technical evaluations with new prospects through helping existing customers expand their use of Temporal in production.</p>\n<p>The nature of our business means you&#39;ll spend significant time helping customers who&#39;ve already adopted Temporal unlock more value by expanding into additional use cases, teams, and workloads. This is a high-velocity, technically deep role.</p>\n<p>You&#39;ll partner with developers, architects, and engineering leaders at fast-moving companies to help them understand how Temporal fits into their existing architecture and prove out value through hands-on technical work.</p>\n<p>You&#39;ll be working in a consumption model where usage grows over time, which means building strong technical relationships and staying engaged with accounts as they scale.</p>\n<p>As an early member of a growing team, you should be comfortable with ambiguity, frequent context switching, and creating leverage through reusable assets that help the broader team move faster.</p>\n<p>Must reside in San Francisco, CA</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_ed4bd662-c67","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Temporal","sameAs":"https://temporal.io/","logo":"https://logos.yubhub.co/temporal.io.png"},"x-apply-url":"https://job-boards.greenhouse.io/temporaltechnologies/jobs/5037692007","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$200,000 - 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Remote Opportunity"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Strong development background with hands-on coding experience in at least one modern language (Go, Java, TypeScript, or Python), Deep understanding of distributed systems (reliability, observability, and fault tolerance), Proven experience in a pre-sales, customer-facing engineering, or solutions architecture role working with technical buyers, Exceptional time management and prioritization skills with the ability to thrive in high-volume environments, Enthusiasm for AI/ML technologies and eagerness to learn about emerging use cases in agentic workflows and LLM orchestration, Experience with workflow engines, event-driven architectures, or orchestration technologies (Temporal, Cadence, or similar), Background articulating the value of commercial SaaS offerings that compete with open source alternatives (Redis, Kafka, Databricks, etc.), Contributions to developer tooling, open source projects, or technical content, Strong cross-functional collaboration skills with the ability to serve as a technical bridge between customers and internal teams, Certifications with any of the major cloud providers (AWS, GCP, or Azure) or foundational AI model providers (OpenAI, Anthropic, or Google)","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":200000,"maxValue":250000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_84761ab6-9fc"},"title":"Solutions Architect, Applied AI (Beneficial Deployments)","description":"<p>As a Solutions Architect, Applied AI (Beneficial Deployments) at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack.</p>\n<p>You will combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.</p>\n<p>Working closely with our Sales, Product, and Engineering teams, you&#39;ll guide customers from initial technical discovery through successful deployment. You&#39;ll leverage your expertise to help customers understand Claude&#39;s capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Partner with account executives across India to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation</li>\n</ul>\n<ul>\n<li>Serve as the primary technical advisor to enterprise customers across India throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams &amp; stakeholders to drive customer success</li>\n</ul>\n<ul>\n<li>Support customers building with both the Claude API and Claude for Work</li>\n</ul>\n<ul>\n<li>Create and deliver compelling technical content tailored to different audiences across India. You will need to be able to spread the gamut from technical deep dives for engineering &amp; development teams up to business value focused conversations with executives</li>\n</ul>\n<ul>\n<li>Guide technical architecture decisions and help customers across India integrate Claude effectively into their existing technology stack</li>\n</ul>\n<ul>\n<li>Help customers develop evaluation frameworks to measure Claude&#39;s performance for their specific use cases</li>\n</ul>\n<ul>\n<li>Identify common integration patterns and contribute insights back to our Product and Engineering teams</li>\n</ul>\n<ul>\n<li>Travel occasionally to customer sites for workshops, technical deep dives, and relationship building</li>\n</ul>\n<ul>\n<li>Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns</li>\n</ul>\n<p>You may be a good fit if you have:</p>\n<ul>\n<li>7+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager</li>\n</ul>\n<ul>\n<li>Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders</li>\n</ul>\n<ul>\n<li>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering &amp; IT teams, and more</li>\n</ul>\n<ul>\n<li>Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders</li>\n</ul>\n<ul>\n<li>Experience designing scalable cloud architectures and integrating with enterprise systems</li>\n</ul>\n<ul>\n<li>Comfortable with python</li>\n</ul>\n<ul>\n<li>Familiarity with common LLM frameworks and tools or a background in machine learning or data science</li>\n</ul>\n<ul>\n<li>Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>\n</ul>\n<ul>\n<li>A love of teaching, mentoring, and helping others succeed</li>\n</ul>\n<ul>\n<li>Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>\n</ul>\n<ul>\n<li>Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems</li>\n</ul>\n<p>Logistics:</p>\n<ul>\n<li>Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience</li>\n</ul>\n<ul>\n<li>Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience</li>\n</ul>\n<ul>\n<li>Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<ul>\n<li>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.</li>\n</ul>\n<ul>\n<li>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.</li>\n</ul>\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.</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>How we&#39;re different:</p>\n<ul>\n<li>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.</li>\n</ul>\n<ul>\n<li>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. 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stakeholders (written and verbal)</li>\n<li>Track record of rapid response to time-sensitive security requests</li>\n<li>Comfort operating across organizational boundaries (Security, People, Legal, IT)</li>\n<li>Exceptional communication, collaboration skills and the ability to lead projects with little guidance</li>\n<li>Demonstrated ability to operate independently with minimal oversight while managing sensitive cases</li>\n</ul>\n<p>Strong candidates may also have:</p>\n<ul>\n<li>Experience working in the technology industry or at/with AI/ML companies</li>\n<li>Experience with counterintelligence investigations and nation-state threat actor TTPs</li>\n<li>Background in open-source intelligence collection and analysis</li>\n<li>Track record of AI/LLM adoption for productivity gains in investigative work</li>\n<li>Experience contributing to a high growth startup environment</li>\n<li>Specialized knowledge of risks unique to the AI sector</li>\n<li>Experience with data exfiltration investigations across multiple vectors (email, cloud, removable media)</li>\n<li>Experience working in government, defense, or high-security environments</li>\n</ul>\n<p>What makes you successful here:</p>\n<ul>\n<li>Entrepreneurial mindset: You see gaps and fill them without being asked</li>\n<li>Technical + human balance: Equal comfort analyzing log data and conducting sensitive interviews</li>\n<li>AI-native approach: You leverage LLMs to work smarter, not just harder</li>\n<li>Mission alignment: You understand AI safety stakes and insider risk&#39;s role in protecting that mission</li>\n<li>Judgment under uncertainty: You make sound decisions with incomplete information</li>\n<li>Clear communicator: You distill complex findings into actionable insights for diverse audiences</li>\n<li>Cross-functional navigator: You build relationships and collaborate effectively across teams</li>\n</ul>\n<p>Annual compensation range for this role is $245,000-$305,000 USD.</p>\n<p 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