You will join a cross-functional Product team, Search Intelligence, which is responsible for optimizing ranking and recommendations for users visiting our website.

You'll be part of the broader Data Science team, which operates across cross-functional domain teams - giving you access to shared knowledge, best practices, and collaboration opportunities beyond your domain.

You’ll collaborate daily with Data Engineers, Analysts, Product Managers, and Back-end Engineers.

You’ll report to the Team Lead, Data Science.

Together, we turn data into actionable insights and innovative technology that powers how millions of guests find and book their perfect holiday home.

Our Tech Stack

• Python • Airflow • dbt • AWS (SageMaker, Redshift, Athena) • MLflow

The Ranking challenge at Holidu

Holidu lists over 4 million vacation rental properties. Our ranking and personalization systems determine which of them our 70+ million annual users see, directly impacting search conversion and business results.

What's live today:

• Multi-stage ranking pipeline: Reinforcement-learning-based cold ranking, contextual re-ranking, and personalized recommendations.

• Cold-start models for new properties with limited behavioral data.

• Personalized recommendations based on user browsing patterns.

Some of the hard problems we're solving:

• Multi-objective optimization: Balancing user relevance, conversion probability, and business value.

• Personalization without history: Most users are anonymous or first-time visitors.

• Cold-start: A significant share of our inventory is new each quarter. How do we surface quality properties before we have behavioral data?

Your role in this journey

You'll shape the ranking and recommendation systems that millions of guests rely on to find their holiday home. With access to extensive datasets and modern ML infrastructure, you'll work end-to-end - from identifying opportunities and prototyping new approaches to shipping models to production and measuring their impact.

• Develop high-impact models and improvements for our ranking, recommendation, and personalization systems - with the freedom to explore new, creative approaches.

• Take models from conception to production, continuously monitor their performance, and iterate to enhance accuracy and efficiency.

• Design and run A/B tests as a core part of ranking development; success is measured by successful experiments per quarter and time-to-decision.

• Collaborate closely with Product Managers and Software Engineers to identify, prioritize, and ship ranking improvements.

• Ensure model reliability in production, measured by online/offline agreement, model and data drift KPIs, latency and uptime SLAs, and automated monitoring coverage.

• Advance our MLOps practices with CI/CD pipelines, retraining workflows, lineage tracking, and documentation.

• Demonstrate leadership in data science projects by driving technical direction, scoping initiatives, and guiding the team's prioritization and project execution.

Your backpack is filled with

• 5+ years of experience as a Data Scientist, with a proven track record of applying ML models to solve real business problems.

• Experience working on ranking models or recommender systems is a strong advantage.

• A degree in Machine Learning, Computer Science, Mathematics, Physics, or a related field.

• Strong foundations in statistics, predictive modeling, and machine learning techniques, with hands-on experience using Python and SQL.

• Experience with Airflow and dbt is a plus.

• Solid understanding of business operations and the ability to translate data insights into clear, actionable outcomes.

• A collaborative mindset and enthusiasm for using data to build world-class products that make a real impact.

• AI Proficiency: You are comfortable using AI to enhance coding, planning, and monitoring. This includes successfully integrating AI tools (such as Claude code, Codex, Copilot, etc.) into your workflow and teaching others to use them efficiently.

Our adventure includes

• Impact: Shape the future of travel with products used by millions of guests and thousands of hosts. At Holidu ideas become products, data drives decisions, and iteration fuels fast learning. Your work matters - and you’ll see the impact.

• Learning: Grow professionally in a culture that thrives on curiosity and feedback. You’ll learn from outstanding colleagues, collaborate across disciplines, and benefit from mentorship, and personal learning budgets - with a strong focus on AI.

• Great People: Join a team of smart, motivated and international colleagues who challenge and support each other. We celebrate wins and keep our culture fun, ambitious and human. Our customers are guests and hosts - people we can all relate to - making work meaningful and energizing.

• Technology: Work in a modern tech environment. You’ll experience the pace of a scale-up combined with the stability of a proven business model, enabling you to build, test, and improve continuously.

• Flexibility: Work a hybrid setup with 50% in-office time for collaboration, and spend up to 8 weeks a year from other inspiring locations. You’ll stay connected through regular events and meet-ups across our almost 30 offices.

• Perks on Top: Of course, we also offer travel benefits, gym discounts, and other perks to keep you energized - but what truly sets us apart is the chance to grow in a dynamic industry, alongside amazing people, while having fun along the way.

Need a sneak peek? Check out the adventure that awaits you on Instagram @lifeatholidu and dive straight into the world of Tech at Holidu for more insights!

Want to travel with us?

Apply online on our careers page! Your first travel contact will be Lucia from HR.

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As a key member of our sales team, you will be responsible for closing net new business with a focus on professionally funded companies, becoming a trusted account advisor by managing accounts and being strategic in both inbound and outbound sales, and engaging with businesses at all points of the sales cycle.

We offer a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. Our offices are located in San Francisco and New York City, and we require a minimum of two coordinated days in the office per week.

Responsibilities:

• Close net new business with a focus on professionally funded companies
• Become trusted account advisors by managing accounts and being strategic in both inbound and outbound sales
• Engage with businesses at all points of the sales cycle, including prospecting, product demonstrations, onboarding, and close
• Develop strategic plans on how to close more companies and generate more revenue
• Focus on self-development with daily training and enablement
• Work closely with Startups Ambassadors to bring in referrals

Requirements:

• 18+ months of Outbound B2B SaaS Sales experience
• 6+ months of B2B SaaS closing experience
• Excels in conversations with c-suite executive decision makers
• Experience carrying quota
• Consistently in the top 10% of the stack ranking
• Proven track record of hitting and exceeding quotas

Compensation: The expected OTE range for this role is USD $122,026 - $152,533.

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Our team works on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You'll work on complex, real-world ML problems at massive scale, and contribute to technical strategy, architecture, and long-term ML roadmap.

Responsibilities:

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment

Basic Qualifications:

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications:

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• 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
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams:

• Ads Measurement Modeling
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Pay Transparency:

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.

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.

The base salary range for this position is: $185,800-$260,100 USD

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Your responsibilities will include:

• Designing, building, and deploying production-grade machine learning models and systems at scale
• Owning the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Building scalable data and model pipelines with strong reliability, observability, and automated retraining
• Working with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partnering cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions

You'll work on a wide range of high-impact problems across the Reddit ecosystem, including recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, and multimodal embedding systems.

To be successful in this role, you'll need:

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions

Preferred qualifications include experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems, familiarity with distributed systems and large-scale data processing, and experience working with real-time systems and low-latency production environments.

At Reddit, we're committed to building a workforce representative of the diverse communities we serve. We're proud to be an equal opportunity employer and are committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

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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.

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.

Our stack includes Python (Django/FastAPI), TypeScript/React, Elasticsearch, PostgreSQL, Redis, dbt, Snowflake, Temporal, and custom ML models. Everything runs on AWS.

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We're looking for a Senior Machine Learning Engineer to join our Monetization team. As a key member of the team, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

Key responsibilities include:

• Building cutting-edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partnering closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search)
• Using data-driven methods and leveraging the unique properties of our data to improve candidate retrieval
• Working in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems

Requirements:

• 2+ years of industry experience applying machine learning methods
• Degree in computer science, statistics, or related field; or equivalent experience
• End-to-end hands-on experience with building data processing pipelines, large-scale machine learning systems, and big data technologies
• Practical knowledge of large-scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Nice to have:

• M.S. or PhD in Machine Learning or related areas
• Publications at top ML conferences
• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
• Expertise in scalable real-time systems that process stream data
• Passion for applied ML and the Pinterest product
• Background in computational advertising

Relocation Statement:

This position is not eligible for relocation assistance.

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Dialpad is the AI-native business communications platform. We unify calling, messaging, meetings, and contact center on a single platform - powered by AI that understands every conversation in real time.

More than 70,000 companies around the globe, including WeWork, Asana, NASDAQ, AAA Insurance, COMPASS Realty, Uber, Randstad, and Tractor Supply, rely on Dialpad to build stronger customer connections using real-time, AI-driven insights.

We’re now leading the shift to Agentic AI: intelligent agents that don’t just analyze conversations but take action by automating workflows, resolving customer issues, and accelerating revenue in real time.

Our DAART initiative (Dialpad Agentic AI in Real Time) is redefining what a communications platform can do.

Visit dialpad.com to learn more.

Being a Dialer

At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more.

We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves.

We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level.

We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic.

Your role

Dialpad’s Product Engineering organization is responsible for building and maintaining the customer-facing features at scale across all of our cloud-native products and services.

Every day, millions of users across the world leverage our technology for communicating effectively and efficiently.

Every engineer on our global engineering team is given the opportunity to take ownership of a large portion of the product where they’re able to see immediate results.

Combining natural language processing and artificial intelligence with world-class cloud computing, the things you’ll create at Dialpad will shape the future of work,enabling companies to work from anywhere and making business communication more human.

Dialpad’s Analytics team owns data pipelines, multiple databases, a modular query layer, and rich FE components to deliver intuitive and powerful end-user-facing analytics experiences that allow Dialpad customers to make data-driven business decisions.

Our teams are highly collaborative and comprise cross-disciplinary professionals, including Product Managers, Designers, QA specialists, as well as Engineers specialising in Data Engineering, Data Science, and Telephony.

This position reports to the Engineering Manager, who is based in Bengaluru, and the role will be based in our Bengaluru, India Office.

The position will require a hybrid working arrangement based out of our Bengaluru office.

What you’ll do

• Contribute to the design, development, and maintenance of information retrieval and distributed systems.

• Build and optimize search engines, including indexers, analyzers, ranking, and re-ranking strategies.

• Work on hybrid search techniques, including dense vector manipulation, rank fusion, and reranking.

• Maintain and enhance highly scalable search platforms with a focus on performance and cost efficiency.

• Ensure high availability, reliability, and fault tolerance in search services.

• Collaborate with cross-functional teams to translate business requirements into technical solutions.

• Develop and optimize real-time distributed systems, microservices, and message-driven architectures.

• Implement and maintain monitoring, alerting, and performance metrics for platform reliability.

• Evaluate and integrate emerging technologies to improve search capabilities.

• Write clean, modular, and well-tested code while following best engineering practices.

• Participate in code reviews to ensure quality, maintainability, and scalability.

• Provide mentorship and technical guidance to junior engineers.

Skills you’ll bring

• 4-7 years of experience in information retrieval or distributed systems engineering.

• Strong understanding of search platforms and experience maintaining search engines at scale.

• Deep knowledge of indexers, analyzers, field mapping, and ranking techniques.

• Experience with NLP/NLU within the context of information retrieval.

• Expertise in dense vector manipulation and optimization.

• Familiarity with hybrid search, rank fusion, and reranking techniques.

• Proficiency in Go and Python 3 (experience with Rust or TypeScript is a plus).

• Strong understanding of distributed systems, microservices, and message-driven architectures.

• Passion for real-time performance optimization and high availability.

• Experience with API design using Swagger, OpenAPI, or equivalent tools.

• Knowledge of gRPC or equivalent RPC protocols.

• Experience with Docker and Kubernetes for containerized deployments.

• Familiarity with cloud platforms (GCP preferred, AWS/Azure optional).

• Hands-on experience with Infrastructure as Code tools like Terraform or Ansible.

• Knowledge of CI/CD frameworks and continuous delivery practices.

Why Join Dialpad

• Work at the center of the AI transformation in business communications

• Build and ship agentic AI products that are redefining how companies operate

• Join a team where AI amplifies every employee’s impact

• Competitive salary, comprehensive benefits, and real opportunities for growth

We believe in investing in our people. Dialpad offers competitive benefits and perks, cutting-edge AI tools, and a robust training program that help you reach your full potential.

We have designed our offices to be inclusive, offering a vibrant environment to cultivate collaboration and connection.

Our exceptional culture, repeatedly recognized as a Great Place to Work, ensures that every employee feels valued and empowered to contribute to our collective success.

Don’t meet every single requirement? If you’re excited about this role and possess the fundamental traits, drive, and strong ambition we seek, but your experience doesn’t meet every qualification, we encourage you to apply.

Dialpad is an equal-opportunity employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment.

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A typical day for this role will involve envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems. You will lead, mentor, challenge, and grow enthusiastic, collaborative software engineers and applied scientists across the organization. You will also raise the AI/ML skillset within the organization, which requires a passion for teaching and mentoring.

To be successful in this role, you will need 12+ years of software engineering experience, with 2+ years of experience in a Principal or Senior Staff Engineer role having ownership responsibility over large-scale software systems. You should have a background in the design and development of scalable AI and ML systems and services, and a deep passion for building ML-powered products.

As a Senior Staff Machine Learning Engineer, you will be an inspiring colleague, a coach, and mentor with experience owning and fostering engineering maturity in multiple organizations. You will be a builder, and implementer, who seeks out high-impact work, and who is proactive, curious, and an excellent communicator.

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As a Machine Learning / AI Engineer, you will design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features. You will also build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.

You will collaborate closely with engineers, researchers, designers, and product managers across multiple teams to deliver high-quality ML-driven features and infrastructure. This is a high-impact, cross-functional role where you will shape both foundational systems and user-facing capabilities.

Key responsibilities include:

• Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features.
• Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.
• Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance.
• Work with product engineers to define and deliver impactful AI features across Figma's platform.
• Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment.
• Explore new ideas at the edge of what's technically possible and help shape the long-term AI vision at Figma.

Requirements include:

• 5+ years of industry experience in software engineering, with 3+ years focused on applied machine learning or AI.
• Strong experience with end-to-end ML model development, including training, evaluation, deployment, and monitoring.
• Proficiency in Python and familiarity with ML libraries like PyTorch, TensorFlow, Scikit-learn, Spark MLlib, or XGBoost.
• Experience designing and building scalable data and annotation pipelines, as well as evaluation systems for AI model quality.
• Experience mentoring or leading others and contributing to a culture of technical excellence and innovation.

Preferred qualifications include:

• Familiarity with search relevance, ranking, NLP, or RAG systems.
• Experience with AI infrastructure and MLOps, including observability, CI/CD, and automation for ML workflows.
• Experience working on creative or design-focused ML applications.
• Knowledge of additional languages such as C++ or Go is a plus, but not required.
• A product mindset with the ability to tie technical work to user outcomes and business impact.
• Strong collaboration and communication skills, especially when working across functions (engineering, product, research).

At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you're excited about this role but your past experience doesn't align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

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Key responsibilities include:

• Developing and deploying ML-based search and discovery relevance models and systems integrated with Databricks' products and services.
• Designing and implementing automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration.
• Collaborating with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience.
• Contributing to building a robust framework for evaluating search ranking improvements - both offline and online.

Requirements include:

• A Bachelor's degree in Computer Science or a related field, with a Master's or PhD preferred.
• 5+ years of experience developing search relevance systems at scale in production or in high-impact research environments.
• Experience applying LLM to search relevance.
• Strong understanding of computer science fundamentals.
• Contributions to well-used open-source projects.

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Responsibilities:

• Lead projects from concept, design, implementation, to rollout, ensuring the highest quality and performance.
• Identify opportunities to enhance ranking capabilities by diving deep into our platform and understanding the needs of our customers.
• Design and develop applied machine learning models for modeled personalization, game taxonomy, and more, from ideation to production deployment.
• Collaborate with data scientists, product managers, and backend software engineers.
• Mentor junior team members, share knowledge, and contribute to the technical growth of the team.
• Provide guidance on machine learning best practices and methodologies.
• Conduct A/B tests and experiments to iterate and fine-tune algorithms and models.
• Stay updated on state-of-the-art algorithmic techniques and recognize promising innovations, adapting them to Reddit's unique platform and community.

Minimum Qualifications:

• 7+ years of experience in a relevant industry or academic background, preferably in a quantitative/modeling or highly scalable computing environment.
• Prior experience with personalized feed ranking.
• Proven track record of delivering complex machine learning projects from conception to deployment, preferably in real-world applications.
• Ability to lead and mentor machine learning engineers or data scientists.
• Strong communication skills to collaborate effectively with cross-functional teams and stakeholders.
• Demonstrated ability to innovate and stay updated with the latest advancements in machine learning and AI.

Preferred Qualifications:

• Experience of orchestrating complicated data pipelines and system engineering on large-scale datasets.
• Proficiency with programming languages and statistical analysis.
• Prior experience with Sequence Modeling, Reinforcement Learning, or Transformer Architecture.
• Experience in Bayesian methodology and experimentation.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs.
• 401k with Employer Match.
• Family Planning Support.
• Gender-Affirming Care.
• Mental Health & Coaching Benefits.
• Flexible Vacation & Paid Volunteer Time Off.
• Generous Paid Parental Leave.

Pay Transparency:

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.

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.

The base salary range for this position is $230,000-$322,000 USD.

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In this role, you will own the quality of results for two distinct but deeply connected 'users': the AI Agent and the Human User. You will optimize the retrieval layer that allows Large Language Models (LLMs) to reason over data they weren't trained on, ensuring they have the 'ground truth' needed to synthesize accurate, high-stakes business actions. You will also improve the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces.

This is a challenging problem that requires balancing traditional keyword-based search with semantic vector search. You will fine-tune ranking models that satisfy both human readability and LLM-ready context. You will also connect the dots across structured SQL tables, unstructured docs, and real-time business metrics.

If you want to solve the hardest problems in data discovery and see your work power the decision-making of thousands of people, let's talk.

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Our team is responsible for building systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You will work on high-impact systems that improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.

As a Senior Machine Learning Engineer, you will:

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment

Basic Qualifications:

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications:

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• 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
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams:

• Ads Measurement Modeling
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

Pay Transparency:

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. To learn more, please visit https://www.redditinc.com/careers/. 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. The base salary range for this position is $216,700-$303,400 USD

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The ideal candidate will have a strong background in information retrieval, machine learning, and software engineering. You will be working on a highly complex and challenging problem, balancing traditional keyword-based search with semantic vector search, and fine-tuning ranking models to satisfy both human readability and LLM-ready context.

Responsibilities:

• Own the quality of results for our AI agents and human users
• Optimize the retrieval layer for LLMs to reason over data they weren’t trained on
• Improve the traditional search experience for employees to find assets and answers through intuitive, high-recall interfaces
• Build the guardrails and relevance scoring to ensure our AI stays grounded in reality

Requirements:

• Strong background in information retrieval, machine learning, and software engineering
• Experience with Lucene/Elasticsearch, embeddings, and ranking algorithms
• Understanding of relevance metrics (nDCG, MRR, Precision@K)
• Ability to work on a highly complex and challenging problem

Benefits:

• Comprehensive benefits and perks that meet the needs of all employees
• Opportunity to work on a highly complex and challenging problem
• Collaborative and dynamic work environment

About Databricks:

Databricks is a data and AI company that provides a platform for unifying and democratizing data, analytics, and AI. Over 10,000 organizations worldwide, including many Fortune 500 companies, rely on Databricks.

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As a Staff Software Engineer for Search Quality, you will drive the technical direction of ranking, relevance, evaluation, and quality initiatives across Databricks' next-generation Search product. You'll design and build the systems, models, and evaluation frameworks that ensure our Search stack delivers accurate, high-quality results across diverse multimodal datasets and query patterns.

The impact you will have:

• Lead the technical vision for Search Quality, shaping the ranking architecture, relevance modeling stack, and evaluation systems that power Databricks' next-generation retrieval experiences.

• Identify and solve challenges in ranking, query understanding, and hybrid retrieval , advancing state-of-the-art techniques in vector, keyword, and multimodal search.

• Design and train production-ready ranking and reranking models with strong guarantees around quality, latency, and resource efficiency.

• Partner closely with research, product, and infra teams to define metrics, evaluation methodologies, and experimentation strategies for new retrieval features and model architectures.

• Drive end-to-end engineering efforts , from early prototyping to production rollout , ensuring correctness, reliability, and measurable improvements to relevance.

• Build and operate resilient, low-latency services for ranking, evaluation, and relevance signal processing.

• Champion excellence in ML and search engineering, mentoring teammates and elevating design, code quality, and scientific rigor across the team.

• Shape Databricks' long-term roadmap for retrieval quality, ranking infrastructure, and the foundations for retrieval-driven AI products.

What we look for:

• 10+ years of experience building large-scale search, ranking, recommendation, or ML-driven relevance systems.

• Deep expertise in Search Quality, including ranking models, signals, query understanding, and evaluation methodologies.

• Strong understanding of relevance metrics and evaluation frameworks.

• Familiarity with vector search, keyword search, hybrid retrieval, and embedding-based semantic retrieval.

• Solid foundation in algorithms, data structures, and system design for performance-critical ranking and retrieval systems.

• Proven ability to deliver high-impact technical initiatives with clear business or product outcomes.

• Strong communication skills and ability to collaborate across teams in fast-moving environments.

• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision.

• Passion for mentoring, growing engineers, and fostering technical excellence.

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This team's work touches every single booking decision on a platform that facilitates hundreds of millions of trips and an incredibly diverse global inventory. You will ship and iterate on AI-powered features that help guests make more confident booking decisions , synthesizing signals from reviews, ratings, and listing data into quality information that is clear, personalized, and trustworthy.

This means working hands-on with Data Science to evaluate model performance and translate outputs into better product decisions, not just defining requirements and handing them off. This role requires close partnership with the Policy, Privacy, and Legal teams , particularly on review integrity, AI-generated content, and trust-related guest-facing features.

You will work especially closely with the quality data platform team to generate and consume accurate quality signals that foster a trusted marketplace, as well as across Design, Engineering, and Data Science to ship and iterate at scale.

This is a critical role that spans the end-to-end guest experience around listing quality information, and the features you build will be part of the experience for every guest who considers booking on Airbnb.

As a Product Manager, you will:

• Develop and execute the product roadmap for Trip Quality Merchandising and AI, with a focus on shipping AI-powered features that improve how guests evaluate listing quality.
• Define product requirements for generative AI features (e.g. listing summaries, quality highlights) and ML ranking systems, including evaluation criteria, guardrails, and iteration plans.
• Partner with Data Science to assess model performance , understanding where outputs are accurate and trustworthy, and where they fall short , and translate those assessments into concrete product improvements.
• Craft the product narrative that inspires teams, leadership, and the company and builds alignment on the quality merchandising strategy.
• Partner with design, engineering, and customer support to deliver features that improve both guest and host experiences.
• Collaborate closely with our Policy, Privacy, and Legal teams on topics that are essential to making Airbnb one of the most trusted marketplaces in the world.

You will need to have:

• 10+ years of product management experience.
• Hands-on track record shipping AI/ML-powered features on consumer products , including generative AI features (LLM-based summarization, content generation) and ML ranking or personalization systems , with direct involvement in defining evaluation criteria and improving model outputs.
• Expert ability to use data and business analysis to inform product strategy and drive decisions.
• Domain familiarity with marketplace trust/quality, search/ranking/relevance, or content/feedback systems is strongly preferred.
• Experience creating product messaging and delivering to customers.
• Demonstrated track record of building cross-functional and executive leadership alignment.
• Experience working on consumer products with marketplace dynamics on a global scale.
• Entrepreneurial track record of taking an idea to reality.
• Excited to lead cross-functional execution, from strategy through shipped product in a fast-paced environment.
• Desire to do individual contributor product management work.
• Excellent written and verbal communication; adept at simplifying complex AI/ML and data concepts for diverse audiences.

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Your work will create the foundational dataset that powers our research by building robust, scalable systems for linking, deduplicating, reconciling, and enriching data at massive scale. This role centres on high-impact bulk ingestion and advanced data linkage. You will design the logic, algorithms, and strategies that transform many independent datasets into a unified, high-quality canonical asset used throughout the company.

You will collaborate closely with ML researchers and product teams, working with tools such as BigQuery, Dataflow/Beam, TFRecords, and,where beneficial,distributed systems frameworks like Ray. Familiarity with ML workflows using JAX or multihost training is a plus, as the datasets you produce will directly support that ecosystem.

Responsibilities:

• Build high-throughput bulk ingestion workflows to integrate datasets from multiple external providers.
• Design and implement scalable entity-resolution solutions, including record linking, deduplication, clustering, and conflict arbitration.
• Create and refine matching logic, decision rules, and similarity functions to align datasets with high accuracy and strong coverage.
• Define and track data quality indicators, such as overlap metrics, match precision/recall, duplicate rates, and completeness.
• Prepare training-ready datasets in formats such as TFRecords, and structure data to meet ML research requirements.
• Develop processing components using Dataflow (Beam) and manage large analytical workloads in BigQuery.
• Leverage frameworks like Ray to accelerate large-scale experiments, feature extraction, and research-oriented data preparation.
• Collaborate with ML researchers to anticipate downstream requirements and evolve linkage strategies as new sources and use cases emerge.

Requirements:

• Experience working with large, heterogeneous datasets from multiple providers or domains.
• Strong background in entity resolution, deduplication, data unification, or related large-scale data integration techniques.
• Proficiency in Python, with an emphasis on efficient, scalable data processing.
• Experience with BigQuery, Google Dataflow/Apache Beam, or similar batch-processing frameworks.
• Familiarity with data validation, normalization, reconciliation, and building consistent views across diverse data sources.
• Ability to craft well-structured matching and decision strategies that balance accuracy, completeness, and computational efficiency.
• Comfortable iterating quickly on pragmatic solutions, balancing correctness with time-to-delivery.
• Clear communication skills and the ability to collaborate closely with ML and research teams.

Nice to Have:

• Knowledge of architecting Google Cloud Platform systems at scale.
• Experience with distributed compute frameworks such as Ray, Spark, or Flink.
• Understanding of JAX-based ML pipelines, multihost training setups, or large-scale data preparation for accelerator-backed workflows.
• Familiarity with TFRecords or other high-volume training data formats.
• Exposure to ranking, clustering, or statistical similarity modeling.
• Experience with Go, NextJS, and/or React Native to contribute to full-stack development.

Why Join Us:

• You will design the core dataset that underpins our research, product development, and generative audio models.
• You'll work on large-scale data challenges that require creativity, algorithmic thinking, and engineering excellence.
• You'll join a small, fast-moving team where your decisions shape the direction of our data and research capabilities.

Benefits:

• Highly competitive salary and equity.
• Quarterly productivity budget.
• Flexible time off.
• Fantastic office location in Manhattan.
• Productivity package, including ChatGPT Plus, Claude Code, and Copilot.
• Top-notch private health, dental, and vision insurance for you and your dependents.
• 401(k) plan options with employer matching.
• Concierge medical/primary care through One Medical and Rightway.
• Mental health support from Spring Health.
• Personalized life insurance, travel assistance, and many other perks.

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are a global company with a diverse workforceREADME

Embedded directly in a product team as search, chat, documents, or audio, you'll improve AI-powered features through rigorous evaluation, prompt and orchestration design, and rapid experimentation. You'll own your domain's AI quality end-to-end: define what "good" looks like, measure it, run experiments, and ship what works.

Responsibilities

• Design and run evaluations for your product area: reference tests, heuristics, model-graded checks tailored to search relevance, chat quality, document understanding, or audio performance.

• Define and track metrics that matter: task success, helpfulness, hallucination proxies, safety flags, latency, cost.

• Own prompt and orchestration design: write, test, and iterate on prompts and system prompts as a core part of your work.

• Run A/B tests on prompts, models, and configurations; analyze results; make rollout or rollback decisions from data.

• Set up observability for LLM calls: structured logging, tracing, dashboards, alerts.

• Operate model releases: canary and shadow traffic, sign-offs, SLO-based rollback criteria, regression detection.

• Improve core behaviors in your product area, whether that's memory policies, intent classification, routing, tool-call reliability, or retrieval quality.

• Create templates and documentation so other teams can author evals and ship safely.

• Partner with Science to diagnose regressions and lead post-mortems.

About you

• 3-4 years of experience; backgrounds that fit well include ML engineers moving closer to product, or software engineers with real AI/ML production experience.

• Strong TypeScript or Python skills - we have both tracks depending on team fit.

• Production LLM experience: prompts, tool/function calling, system prompts.

• Hands-on with evals and A/B testing; you can design metrics, not just run them.

• Comfortable implementing directly in product code, not only notebooks.

• Observability experience: logging, tracing, dashboards, alerting.

• Product mindset: form hypotheses, run experiments, interpret results, ship.

• Clear communication, autonomous, and oriented toward production impact over experimentation for its own sake.

It would be ideal if you also have:

• Safety systems experience: moderation, PII handling/redaction, guardrails.

• Release operations: canary/shadowing, automated rollbacks, experiment platforms.

• Prior work on search ranking, chat systems, document AI, or audio ML features.

Hiring Process

• Introduction call - 30 min

• Hiring Manager interview - 30 min

• Technical Rounds - Live-coding Interview - 45 min - AI Engineering Interview - 45 min

• Culture-fit discussion - 30 min

• References

By applying, you agree to our Applicant Privacy Policy.

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LLM & AI Pipeline Engineering - Design, build, and maintain production-grade LLM integration pipelines , including retrieval-augmented generation (RAG), prompt engineering, output parsing, and chain orchestration.

Develop and operate AI features within Jeeves's core financial products: spend categorization, document extraction, anomaly detection, financial Q&A, and automated reconciliation.

Implement structured output validation, fallback handling, and confidence scoring to ensure AI decisions meet reliability standards for financial use cases.

Evaluate and integrate AI frameworks and tools (LangChain, LlamaIndex, OpenAI API, Anthropic API, HuggingFace, vector databases) and advocate for the right tool for the job.

Establish prompt versioning and evaluation practices to ensure AI outputs remain accurate and consistent as models and data evolve.

Retrieval & Vector Search - Design and maintain vector search pipelines using databases such as Pinecone, Weaviate, or pgvector to power semantic search and RAG-based features.

Build document ingestion and chunking pipelines for Jeeves's financial data , processing invoices, receipts, policy documents, and transaction records.

Optimize retrieval quality through embedding model selection, chunk strategy, metadata filtering, and re-ranking techniques.

ML Model Serving & Operations - Collaborate with data scientists to take trained ML models from experimental notebooks to production serving infrastructure.

Build and maintain model serving endpoints with appropriate latency SLOs, input validation, and output monitoring.

Implement model performance monitoring and data drift detection to ensure production models remain accurate over time.

Support model retraining workflows by designing clean data pipelines and feature engineering that can be continuously updated.

Backend Integration & Reliability - Integrate AI services cleanly with Jeeves's backend microservices , designing clear API contracts, circuit breakers, and graceful degradation patterns.

Write high-quality, testable backend code in Python or Go/Node.js to power AI-integrated features.

Instrument AI components with structured logging, distributed tracing, latency dashboards, and alerting to ensure operational visibility.

Collaboration & Growth - Partner with Product, Backend Engineering, and Data Science to define the AI roadmap and translate requirements into reliable systems.

Contribute to a culture of quality by writing design docs, reviewing peers' AI system designs, and sharing learnings openly.

Help grow the AI engineering practice at Jeeves by establishing patterns, tooling, and best practices that the broader team can build on.

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Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry.

The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning products are robust, scalable, and cost-efficient.

Responsibilities:

Partner with stakeholders to scope problems and identify the right solution - whether leveraging existing AI tools or building custom workflows & solutions.

Design and implement agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack.

Build and maintain production ML pipelines and services for non-GenAI use cases (e.g. recommender systems, customer segmentation models, marketing optimisation modules, leveraging supervised, unsupervised and/or econometric modelling approaches).

Develop APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability.

Implement CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance.

Establish robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations.

Drive and evangelize best practices, reusable templates, and documentation to scale AI/ML delivery across the business.

Collaborate with data engineers, data scientists, front & back-end engineers, product managers, legal & infosec colleagues to deliver impactful solutions end-to-end.

Who you will work with

The AI & ML Engineer Lead and the wider data team.

About you

The role requires a blend of technical depth and product sense, including:

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Strong Python engineering skills (FastAPI, testing, typing) and experience with cloud-native development (GCP preferred).

Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph.

Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring.

Proven experience deploying and operating ML systems in production (batch and real-time).

Familiarity with RAG architectures, prompt engineering, and evaluation techniques.

Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling).

Excellent communication skills and ability to work with non-technical stakeholders.

In addition to the above, we would LOVE if you have:

Experience with vector databases and retrieval strategies.

Knowledge of recommender systems and ranking models.

Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize).

Exposure to feature stores, data lineage, and observability stacks.

Experience in e-commerce or retail environments.

Demonstrable ability to weigh up build/build/configure decisions in the LLM space.

Why join us?

Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves.

We’re a hybrid model with flexibility, allowing you to work how best suits you.

25 days holiday (plus bank holidays) with an additional day to celebrate your birthday.

Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey.

Financial security and planning with our pension and life assurance for all.

Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues.

Bring your furry friend to work with you on our allocated dog friendly days and spaces.

And not to forget our generous product discount and gifting!

At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves.

We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce.

By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.

If you want to learn more about life at Charlotte Tilbury Beauty please follow our LinkedIn page!

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You will play a pivotal role in exploring how to integrate data from recommendation domains into foundation models, enabling new capabilities through data curation, Supervised Fine-Tuning (SFT), Reinforcement Learning (RL) training, and more.

Key responsibilities:

• Research and develop key technologies such as Semantic IDs, generative retrieval/ranking, large user models.
• Build prototypes to demonstrate the 'art of the possible' for recommendation systems using the newest AI advances.
• Work closely with product teams to translate research breakthroughs into deployed solutions for flagship products, tackling real-world challenges at an industrial scale through new recipes.

We are seeking a Research Scientist who can drive new research ideas from conception and experimentation through to productionisation. In this rapidly shifting landscape, we regularly invent novel solutions to open-ended problems. You should be flexible, adaptable, and comfortable pivoting when ideas don't work out.

In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:

• PhD in Machine Learning, Computer Science, or a relevant field (or equivalent practical research experience).
• A proven track record of research excellence (e.g., publications at top-tier venues like NeurIPS, ICML, ICLR, or significant industry contributions), ranging from recent graduates to experienced researchers.
• Strong software engineering skills to complement your research background.

In addition, the following would be an advantage:

• Proven track record of building recommender / search systems and/or successfully deploying novel deep learning algorithms at industrial scale.
• Skilled in LLM post-training algorithms and infra, with proficiency in JAX.
• Strong communication skills with a demonstrated ability to drive cross-functional projects and collaborate effectively across organizational boundaries.

At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options.

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At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We are a global company with teams distributed between France, USA, UK, Germany, and Singapore. Our diverse workforce thrives in competitive environments and is committed to driving innovation.

Role Summary

Embedded directly in a product team as search, chat, documents, or audio, you'll improve AI-powered features through rigorous evaluation, prompt and orchestration design, and rapid experimentation. You'll own your domain's AI quality end-to-end: define what 'good' looks like, measure it, run experiments, and ship what works.

Responsibilities

• Design and run evaluations for your product area: reference tests, heuristics, model-graded checks tailored to search relevance, chat quality, document understanding, or audio performance.
• Define and track metrics that matter: task success, helpfulness, hallucination proxies, safety flags, latency, cost.
• Own prompt and orchestration design: write, test, and iterate on prompts and system prompts as a core part of your work.
• Run A/B tests on prompts, models, and configurations; analyze results; make rollout or rollback decisions from data.
• Set up observability for LLM calls: structured logging, tracing, dashboards, alerts.
• Operate model releases: canary and shadow traffic, sign-offs, SLO-based rollback criteria, regression detection.
• Improve core behaviors in your product area, whether that's memory policies, intent classification, routing, tool-call reliability, or retrieval quality.
• Create templates and documentation so other teams can author evals and ship safely.
• Partner with Science to diagnose regressions and lead post-mortems.

About You

• 3-4 years of experience; backgrounds that fit well include ML engineers moving closer to product, or software engineers with real AI/ML production experience.
• Strong TypeScript or Python skills - we have both tracks depending on team fit.
• Production LLM experience: prompts, tool/function calling, system prompts.
• Hands-on with evals and A/B testing; you can design metrics, not just run them.
• Comfortable implementing directly in product code, not only notebooks.
• Observability experience: logging, tracing, dashboards, alerting.
• Product mindset: form hypotheses, run experiments, interpret results, ship.
• Clear communication, autonomous, and oriented toward production impact over experimentation for its own sake.

Benefits

• Competitive salary and equity package
• Health insurance
• Transportation allowance
• Sport allowance
• Meal vouchers
• Private pension plan
• Generous parental leave policy

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We are seeking a highly skilled Data Scientist III to join our EADP Gameplay Services team. As a Data Scientist III, you will play a key role in analysing complex matchmaking datasets to identify patterns, trends, and opportunities that drive data-informed business decisions.

We Are EA

Our platform powers online features for EA’s games, serving millions of users each day. We live, breathe, and dream about how we can make every player’s multiplayer experience memorable. We develop services and SDKs in collaboration with EA’s game studios for matchmaking, stats and leaderboards, achievements, game replays, VOIP, and game networking.

Opportunity Ahead

Our primary mission is to enrich the player’s gaming experience by meticulously optimising the matchmaking process. We believe that effective matchmaking is the cornerstone of any successful multiplayer gaming experience, and we are committed to perfecting this aspect of our service. We continuously reflect and probe various elements to ensure the player’s gaming encounters are both fun and challenging

Key Responsibilities

• Analyse complex matchmaking datasets to identify patterns, trends, and opportunities that drive data-informed business decisions.
• Perform data exploration, mining, and feature engineering to create high-quality datasets for model development.
• Ensure data integrity and governance through robust validation, preprocessing, and quality assurance processes.
• Own model lifecycle including retraining, validation, performance monitoring, and scalability improvement.
• Define experimentation strategy (A/B testing, causal inference) and measure impact on core gameplay KPIs
• Partner with product, business, and engineering to identify new data acquisition opportunities.
• Create reusable analytical tools, libraries, and metrics that enable data-driven decisions.
• Collaborate with data engineers and software engineer across teams to serve their data needs.
• Evangelise data as a first-class citizen through documentation, standards, and reviews.

Must Have Skills

• Bachelor’s or master’s degree in computer science, Data Science, AI/ML, Statistics, or a related field (or equivalent professional experience)
• 5+ years of experience in data science, analytics, or ML engineering with a strong record of deploying scalable ML solutions.
• Solid understanding of statistical modelling, including probability distributions, regression analysis, and hypothesis testing.
• Strong understanding of experimentation design and A/B testing frameworks
• Expert proficiency in Python frameworks (PyTorch, Scikit-learn).
• Experience with model monitoring and drift detection
• Experience in handling large-scale and high-dimensional datasets using distributed data processing tools (Spark, Snowflake, Databricks).
• Strong communication skills with the ability to translate complex models into business impact.

Desirable Skills

• Experience in gaming analytics or player behaviour modelling
• Experience building recommendation or ranking systems
• Experience with cloud platforms (AWS/GCP/Azure)

What’s in it for you? Glad you asked!

We love to brag about our great perks like Global fitness program, Sodexo (Food Coupons), Parental Insurance & Medical, Accident & life insurance and since we realise it takes world-class people to make world-class games, we offer competitive compensation packages and a culture that thrives off creativity and individuality. At EA, we live the “work hard/play hard” credo every day.

_About Electronic Arts_

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

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Constructor is a U.S. based company that develops a next-generation platform for search and discovery in ecommerce, built to optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents.

About the Team

The Ranking team, within the Machine Learning chapter, plays a central role in implementing algorithms that optimize our customers' business KPIs like revenue and conversion rates. We focus on metrics over features, supplying our ranking algorithms with powerful capabilities that bring value to our customers.

Role Details

Design and Develop ML-Based Ranking Solutions

As a Machine Learning Engineer on the Ranking team, your primary focus will be to enhance the quality of our ranking systems, ensuring that search, browse, and autocomplete experiences are highly relevant, personalized, and diverse. You will work on building state-of-the-art ranking algorithms that improve user experience and drive critical business metrics such as conversion, user engagement, and revenue growth.

Improve Ranking Quality

You will analyze ranking performance and identify gaps in search, browse, and autocomplete experiences, focusing on relevance, personalization, attractiveness, diversification, and other quality signals.

Innovate and Optimize Ranking Algorithms

You will proactively propose new machine learning models, algorithms, and features to advance the ranking pipeline, improve ranking quality, and meet evolving business needs.

Collaboration with Cross-Functional Teams

You will collaborate with technical and non-technical business partners to develop / update ranking functionalities (both within and outside the team)

Requirements

Hard Skills

• At least 4 years of experience with Python for machine learning and backend development
• At least 4 years of experience developing, deploying, and maintaining machine learning models with a strong focus on ranking systems for search, recommendations, or similar applications
• Experience in large-scale ML model training, evaluation, and optimization, with a focus on real-time inference and serving
• Experience with big data frameworks such as Spark for processing large datasets and integrating them into ML pipelines
• Proficiency in using tools like SQL, PySpark, Pandas, and other frameworks to extract, manipulate, and analyze data
• Experience with data pipeline orchestration tools like Airflow or Luigi to manage and automate workflows for ML training and signal delivery
• Experience working on ranking algorithms that optimize metrics such as relevance, conversion rates, personalization, user engagement, RPV is a plus

Soft Skills

• Experience collaborating in cross-functional teams
• Experience leading projects to success
• Excellent English communication skills
• Enjoy helping others around you grow as developers and be successful
• Pick up new ideas and technologies quickly, love learning and talking to others about them
• Love to experiment and use data and customer feedback to drive decision making

Benefits

• Unlimited vacation time
• Fully remote team
• Work from home stipend
• Apple laptops provided for new employees
• Training and development budget for every employee, refreshed each year
• Maternity & Paternity leave for qualified employees
• Work with smart people who will help you grow and make a meaningful impact
• Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results
• Stock options
• Regular team offsites to connect and collaborate

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The Personalization team, within the Machine Learning Chapter and Engineering Department, plays a central role in implementing algorithms that utilize personalization signals to optimize for business KPIs like revenue & conversions.

You will work closely with engineers and product managers to define success, uncover insights, and influence roadmap decisions through data. Your work will help shape innovative user experiences that drive business KPIs, interpret user behavior, and drive product and algorithm improvements.

Challenges you will tackle

• Understand Shopper Behavior: Investigate how product changes affect user behavior and conversion metrics. Use SQL, Python, and Spark to uncover usage patterns, anomalies, and opportunities for optimization.
• Design & Validate Metrics: Define new metrics to measure personalization, and model performance. Ensure metrics align with user experience and business goals through rigorous validation.
• Build Analytics Infrastructure: Create scalable dashboards and reporting tools for product, engineering, and leadership teams. Develop debugging tools to explain ranking decisions and identify performance issues.
• Drive Data-Informed Decisions: Partner cross-functionally to design experiments, validate hypotheses, and communicate insights that directly influence product roadmap and ML strategy.

Requirements

• 3+ years analyzing complex experiments and extracting actionable insights from large, noisy datasets. Experience with statistical testing and practical experiment design.
• Write optimized SQL queries for terabyte-scale data extraction and transformation. Proficiency with distributed systems like Spark for large-scale data processing.
• Strong skills in exploratory analysis and building internal tools. Experience with data science libraries and automation.
• Understanding of ML pipelines, training data quality, and ranking/recommendation metrics. Familiarity with search relevance and personalization concepts.
• Design metrics that accurately reflect model and product performance. Ensure alignment between technical metrics and business outcomes.
• Create compelling dashboards using Tableau, Looker, or custom dashboards in Python. Present complex findings clearly to both technical and executive audiences.
• Influence product and engineering decisions through data storytelling. Collaborate effectively across teams to drive ML and product improvements.
• Deep curiosity about user behavior and business impact. Connect algorithm changes to real-world customer outcomes.

Benefits

• Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year
• Fully remote team - choose where you live
• Work from home stipend! We want you to have the resources you need to set up your home office
• Apple laptops provided for new employees
• Training and development budget for every employee, refreshed each year
• Maternity & Paternity leave for qualified employees
• Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results
• Stock options - offered in addition to the base salary
• Regular team offsites to connect and collaborate

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We're looking for a Senior Applied Scientist to lead end-to-end science for grounding: inventing retrieval and attribution methods, defining factuality/faithfulness metrics, and shipping production models and APIs that scale to billions of queries. You'll partner closely with engineering, product, research, and customers to deliver fast, reliable, and explainable answers with source citations across a diverse set of domains and modalities.

As a team, we value curiosity, pragmatic rigor, and inclusive collaboration. We believe great systems emerge when scientists and engineers co-design metrics, models, and infrastructure—and when we obsess over customer impact, privacy, and safety.

Responsibilities Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact. Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images. Builds citation and provenance systems (e.g., passage highlighting, quote-level alignment, confidence scoring) to reduce hallucinations and increase user trust. Leads experimentation and evaluation using A/B testing, interleaving, NDCG, MRR, precision/recall, and calibration curves to guide measurable trade-offs. Advances tool-augmented grounding through schema-aware retrieval, function calling, knowledge graph joins, and real-time connectors to databases, cloud object stores, search indexes, and the web. Partners with platform engineering to productionize models with scalable inference, embedding services, feature stores, caching, and privacy-compliant multi-tenant systems. Nurtures collaborative relationships with product and business leaders across Microsoft, influencing strategic decisions and driving business impact through technology. Authors white papers, contributes to internal tools and services, and may publish research to generate intellectual property. Bridges the gap between researchers (e.g., Microsoft Research) and development teams, applying long-term research to solve immediate product needs. Leads high-stakes negotiations to ensure cutting-edge technologies are applied practically and effectively. Identifies and solves significant business problems using novel, scalable, and data-driven solutions. Shapes the direction of Microsoft and the broader industry through pioneering product and tooling work. Mentors applied scientists and data scientists, establishing best practices in experimentation, error analysis, and incident review. Collaborates cross-functionally with PMs, research, infrastructure, and security teams to align on milestones, SLAs, and safety protocols. Communicates clearly through design documentation, progress updates, and presentations to executives and customers. Contributes to ethics and privacy policies, identifies bias in product development, and proposes mitigation strategies.

Qualifications Required Qualifications: Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Minimum of 4 years of hands-on experience designing and building search, retrieval, or ranking systems. Proven track record of shipping LLM-powered or Retrieval-Augmented Generation (RAG) systems into production environments. Solid coding skills and solid foundation in machine learning, with the ability to implement and optimize models effectively. Demonstrated ability to lead through ambiguity, make principled trade-offs, and deliver measurable impact in cross-functional, fast-paced settings. Preferred Qualifications: Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL. Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL). Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects.

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As an infrastructure engineer at Cursor, you will be responsible for building highly-available distributed systems, dealing with the woes of scaling to millions of programmers, and working with various databases, proxies, caches, task queues, and orchestration systems. You will also be involved in shipping infra for safely computing import graphs and shadow lints.

Some sample projects you may work on include creating a retrieval system that processes 10,000,000,000+ files, staring at esoteric flame graphs to performance engineer our reranking library, and working with many databases, proxies, caches, task queues, and orchestration systems.

We're a team that enjoys spirited debate, crazy ideas, and shipping code. We're looking for people who are truth-seeking, passionate, and creative, and who are comfortable working in a flat organisational structure.

Our offices are located in North Beach, San Francisco and Manhattan, New York, and are replete with well-stocked libraries. We're an in-person team, and we enjoy working together to build something amazing.

If you're passionate about building highly-available distributed systems, and you're looking for a challenging and rewarding role, we'd love to hear from you.

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Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $250K – $555K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

OpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance human creativity, and solve complex problems.

About the Role

As a Research Engineer in OpenAI's Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.

In this role, you will:

• Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.

• Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.

• Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.

• Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.

• Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.

You might thrive in this role if you:

• Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field.

• Demonstrated experience in deep learning and transformers models

• Proficiency in frameworks like PyTorch or Tensorflow

• Strong foundation in data structures, algorithms, and software engineering principles.

• Experience with search relevance, ads ranking or LLMs is a plus.

• Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization

• Excellent problem-solving and analytical skills, with a proactive approach to challenges.

• Ability to work collaboratively with cross-functional teams.

• Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

• Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Research Engineer, Notifications

Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $295K – $680K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The ChatGPT team works across research, engineering, product, and design to bring OpenAI’s technology to the world.

We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products.

About the Role

We are looking for a Machine Learning Engineer to join our Notifications team, focused on building and scaling intelligent notification systems that provide real value to users even when they are not actively on the product. This role will be central to shaping how ChatGPT communicates proactively and helpfully with users—surfacing the right content, at the right time, through the right channel.

You will work on designing and implementing ranking and recommendation systems that leverage both classical ML techniques and large language models (LLMs) to optimize notification relevance, timeliness, and user experience. The ideal candidate has strong ML fundamentals, experience shipping ranking or recommendation systems in production, exposure to LLMs, and sharp product intuition. You should be comfortable operating across research and product boundaries: thinking from first principles, running rigorous experiments, and building scalable systems.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Design and build end-to-end ranking and recommendation systems for notifications, from modeling to evaluation and deployment.

• Apply and adapt LLMs to ranking problems, including prompt-based approaches and fine-tuning.

• Develop experiments to evaluate notification relevance, user value, and long-term impact, working closely with product, data science, and engineering teams.

• Collaborate with research teams to leverage the latest modeling techniques while balancing practical constraints of production systems.

• Build robust offline and online evaluations to measure system improvements and user outcomes.

• Contribute to the broader Growth ML stack and help set technical direction for intelligent user engagement systems.

You might thrive in this role if you:

• Have hands-on experience building and deploying ranking, recommendation, or personalization systems at scale.

• Have a deep understanding of machine learning and its applications, with exposure to LLMs and their integration into product experiences.

• Are experienced in experimentation, A/B testing, and analyzing impact on user behavior and business metrics.

• Are comfortable diving into large ML codebases, designing evaluations, and debugging complex modeling issues.

• Thrive in dynamic, fast-changing environments and can think from first principles to design elegant solutions.

• Have strong product intuition and can balance modeling sophistication with product impact.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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Microsoft are looking for a highly experienced Principal Software Engineer to join their Ads Engineering Platform team to design and build next-generation Ads products that drive revenue growth and create innovative advertising experiences for users and advertisers.

About the Role

We are seeking a highly experienced software engineer to join our Ads Engineering Platform team to design and build next-generation Ads products that drive revenue growth and create innovative advertising experiences for users and advertisers. You will play a key role in evolving the core capabilities of our ad-serving infrastructure—the engine that powers advertising across Bing Search, MSN, Microsoft Start, and shopping experiences in Microsoft Edge. Our serving stack operates at massive global scale, delivering millions of ad requests per second through a geo-distributed, low-latency system that integrates real-time bidding, intelligent ranking, and ML-driven decisioning pipelines. We leverage a mix of CPU and GPU-based inference to balance latency, throughput, and cost efficiency. This role combines product innovation, distributed systems architecture, and performance engineering. You will help shape both new monetization capabilities and the next generation of model serving infrastructure that powers them.

Accountabilities

• Design and build new Ads products and monetization capabilities that unlock incremental revenue and enhance advertiser and end-user experiences.
• Lead the development of large-scale, distributed online serving systems to process millions of ad requests per second with ultra-low latency and high reliability.

The Candidate we're looking for

Experience:

• 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Proficient experience designing and operating real-time online serving or ranking systems.
• Proficient understanding of distributed systems fundamentals: concurrency, multi-threading, memory management, networking, and fault tolerance.

Personal attributes:

• Demonstrated ability to diagnose performance bottlenecks and improve latency, throughput, and cost efficiency in high-traffic systems.

Benefits

• Competitive salary range of $163,000 - $296,400 per year.
• Benefits and other compensation.
• Opportunities for professional growth and development.

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Microsoft AI are looking for a talented Senior Applied Scientist at their Beijing office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technologies. You'll work directly with leadership to shape the company's direction in the search and AI innovation markets.

About the Role

We are looking for a Senior Applied Scientist to lead the transition of news e2e tech stack to new architect tailored for grounding, which can power news search experience across Bing, Copilot and 3rd party customers faster with better quality and capabilities. The successful candidate will design and build scalable, high-performance platform and grounding services for real-time processing of streaming news content and serving user queries with low latency. They will apply AI and machine learning to solve challenging problems in news Index, content understanding, query understanding, trending detection, ranking, and quality improvement for relevance, freshness, and authority, especially for grounding scenario.

Accountabilities

• Design and build scalable, high-performance platform and grounding services for real-time processing of streaming news content and serving user queries with low latency.
• Apply AI and machine learning to solve challenging problems in news Index, content understanding, query understanding, trending detection, ranking, and quality improvement for relevance, freshness, and authority, especially for grounding scenario.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Technical skills:

• Solid background in platform, AI/ML, including experience with search platform, grounding platform, ranking systems, natural language processing, with more than 4 years of working experience.
• Proficiency in programming languages such as C++, C#, Java, or Python, and familiarity with distributed systems.

Personal attributes:

• Passion for news and AI-driven innovation, with an understanding of user needs in news consumption.
• Ability to work in a fast-paced environment and collaborate across disciplines.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.

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Microsoft AI are looking for a talented Senior Product Manager at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI era.

About the Role

As a Senior Product Manager, you will contribute to defining a product area by understanding user needs and behaviors, writing product requirements, and supporting end-to-end development, launches, and iterations. You will identify long-term investment opportunities and drive business impact across the organization. You will work through roadblocks and help teams ship quickly and iteratively. You will translate business goals into product strategy, user experience, and technical requirements in collaboration with UX and engineering. You will define success metrics, support experimentation, and use data to guide decisions. You will dive into data to understand user behavior, product performance, and new opportunities. You will communicate clearly and collaborate effectively across cross-functional teams. You will model our culture and values in daily work.

Accountabilities

• Contribute to defining a product area by understanding user needs and behaviors, writing product requirements, and supporting end-to-end development, launches, and iterations.
• Identify long-term investment opportunities and drive business impact across the organization.

The Candidate we're looking for

Experience:

• 5+ years experience in product/service/program management or software development.

Technical skills:

• Experience with AI.
• Experience with Grounding, Ranking, Query Understanding.
• Experience in the Search space.

Personal attributes:

• Strong communication and collaboration skills.
• Ability to work in a fast-paced environment.

Benefits

• Competitive salary.
• Comprehensive benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Recognition and rewards for outstanding performance.

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Microsoft AI are looking for a talented Member of Technical Staff - Principal Backend Engineer, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Principal Backend Engineer, you will design and evolve large-scale data architectures that support Copilot memory and personalization, spanning batch, streaming, and serving paths. You will build and operate high-quality personalization and memory data pipelines, including signal ingestion, normalization, enrichment, aggregation, memory generation, and full lifecycle management. You will enable memory and personalization features by exposing well-designed datasets, APIs, and feature interfaces for downstream product and ML consumers. You will work closely with PMs, applied ML, and product engineering to translate product intent into robust data systems and measurable outcomes. You will act as a technical leader for memory and personalization data systems, influencing architecture and standards across multiple teams. You will lead design reviews, unblock complex technical problems, and make principled trade-offs in ambiguous spaces.

Accountabilities

• Design and evolve large-scale data architectures that support Copilot memory and personalization, spanning batch, streaming, and serving paths.
• Build and operate high-quality personalization and memory data pipelines, including signal ingestion, normalization, enrichment, aggregation, memory generation, and full lifecycle management.

The Candidate we're looking for

Experience:

• 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Experience building and deploying machine learning or large language model (LLM) applications at scale.
• Experience designing and implementing large-scale embedding, retrieval, and ranking systems.

Personal attributes:

• Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year.

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Microsoft AI are looking for a talented Member of Technical Staff - Principal Platform Engineer, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Principal Platform Engineer, you will design and build large-scale Copilot memory and personalization systems leveraging search, embeddings, retrieval, ranking, and Retrieval-Augmented Generation (RAG). You will apply subject-matter expertise in cross-product features, collaborating with appropriate stakeholders to drive project plans, release plans, and deliverables across multiple groups. You will hold accountability as a Designated Responsible Individual (DRI), mentoring engineers across products/solutions, working on-call to monitor system/product/service for degradation, downtime, or interruptions.

Accountabilities

• Design and build large-scale Copilot memory and personalization systems leveraging search, embeddings, retrieval, ranking, and Retrieval-Augmented Generation (RAG).
• Apply subject-matter expertise in cross-product features, collaborating with appropriate stakeholders to drive project plans, release plans, and deliverables across multiple groups.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Experience building and deploying machine learning or large language model (LLM) applications at scale.
• Experience designing and implementing large-scale embedding, retrieval, and ranking systems.

Personal attributes:

• Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year.

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Microsoft AI are looking for a talented Senior Applied Scientist at their Suzhou office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technologies. You'll work directly with leadership to shape the company's direction in the search and AI innovation markets.

About the Role

We are looking for a Senior Applied Scientist to design and build scalable, high-performance platform and grounding services for real-time processing of streaming news content and serving user queries with low latency. You will apply AI and machine learning to solve challenging problems in news Index, content understanding, query understanding, trending detection, ranking, and quality improvement for relevance, freshness, and authority, especially for grounding scenario. You will act as a designated responsible individual (DRI), work with partners and v-team members to understand requirements, define roadmap, lead execution, unblock issues, deliver mission on time. You will proactively learn and leverage engineer excellence practice from partner teams, build collaboration with partners. You will maintain system performance, security and compliance.

Accountabilities

• Design and build scalable, high-performance platform and grounding services for real-time processing of streaming news content and serving user queries with low latency.
• Apply AI and machine learning to solve challenging problems in news Index, content understanding, query understanding, trending detection, ranking, and quality improvement for relevance, freshness, and authority, especially for grounding scenario.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Technical skills:

• Solid background in platform, AI/ML, including experience with search platform, grounding platform, ranking systems, natural language processing, with more than 4 years of working experience.
• Proficiency in programming languages such as C++, C#, Java, or Python, and familiarity with distributed systems.

Personal attributes:

• Passion for news and AI-driven innovation, with an understanding of user needs in news consumption.
• Ability to work in a fast-paced environment and collaborate across disciplines.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Flexible working hours and remote work options.

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Microsoft are looking for a talented Senior Applied Scientist at their Beijing office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising online advertising technology. You'll work directly with leadership to shape the company's direction in the advertising market.

About the Role

As a Senior Applied Scientist, you will play a key role in driving algorithmic and modeling improvement to the system. You will analyze performance and identify opportunities based on offline and online testing. You will develop and deliver robust and scalable solutions. You will make direct impact to both user and advertisers experience. You will increase the revenue for Bing ads. You will have good communication, collaboration, and analytical skills.

Accountabilities

• Play a key role in driving algorithmic and modeling improvement to the system.
• Analyze performance and identify opportunities based on offline and online testing.
• Develop and deliver robust and scalable solutions.
• Make direct impact to both user and advertisers experience.
• Increase the revenue for Bing ads.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Technical skills:

• Good design and problem-solving skills to handle challenging tasks independently.
• Excellent self-learning ability to try new ideas from textbooks or research papers and apply them to real business scenario of the assigned tasks.

Personal attributes:

• Self-motivated with solid passion on machine learning and related tasks.

Benefits

• Work from the office at least four days per week.
• Health and wellbeing benefits.
• Professional development opportunities.
• Financial benefits (bonus, equity, pension, etc.).
• Cultural perks (team events, office amenities, etc.).

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What you'll do

• Apply state-of-the-art ML and LLM techniques to solve problems spanning:
• Personalization (LLM memory, context summarization, retrieval and ranking);
• Query Understanding (intent modeling, rewriting, agentic decomposition);
• Content Discovery (feed ranking and surfacing)
• Rigorously evaluate LLM/ML models with both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact.
• Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement.
• Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements.
• Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle.

What you need

• 5+ years experience building and shipping robust ML/AI models for large-scale, user-facing or data-driven products.
• Deep expertise in deep learning (PyTorch, TensorFlow, JAX), LLMs, information retrieval, content summarization, recommendation systems, NLP, and/or ranking.
• Strong software engineering skills (Python, production-quality codebases, collaborative development).
• In-depth experience with the full ML lifecycle: data analysis, feature engineering, iterative model development, rigorous evaluation, and ongoing monitoring/improvement.
• Proven collaborator and communicator; excels in high-velocity, cross-functional teams.
• Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI.
• BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience).

Bonus Points For

• Experience with LLM prompt engineering, Retrieval-augmented generation (RAG) based systems.
• Experience in large scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking, etc).
• Open-source or published contributions in ML, NLP, IR, or relevant research fields.

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