Key Responsibilities: Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. Collaborate 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. Contribute to building a robust framework for evaluating search ranking improvements - both offline and online.

What We’re Looking For: BS+ (M.S. or PhD preferred) in Computer Science, or a related field. 6+ years experience developing search relevance systems at scale in production or in high-impact research environments. Experience applying LLM to search relevance - Experience in one or more of the following: Query understanding NLP Text mining Recommendations Personalization Discovery Conversational AI Strong understanding of computer science fundamentals. Contributions to well-used open-source projects.

Why Join Us? At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts.

About Databricks Databricks is the data and AI company. More than 10,000 organisations worldwide , including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 , rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI.

Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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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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Responsibilities:

• Deliver on technical initiatives that have significant company-wide impact
• Set technical direction for the broader ML and Search teams at Reddit, able to identify opportunities and influence strategy for all of Reddit
• Mentor and grow Staff and Senior Staff engineers
• Create a strong healthy engineering culture

Qualifications:

• 15+ years of industry experience building systems for relevance-driven products
• Subject matter expert in Search, recommendation, and ML systems, able to solve complex problems in these domains that few others can
• Deep understanding of how to build a sustainable software system at a large-scale engineering organization
• Experience in influencing larger (100+ engineers) organizations on technical direction/best practices
• Experience working with cross-functional teams such as design, product, business, and data teams to deliver great experiences
• Strong focus on user experience, usability, scalability, reliability, and quality
• High empathy, excellent communication skills, and the ability to find compromise working across the entire engineering org

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 and coaching benefits
• Flexible vacation and paid volunteer time off
• Generous paid parental leave

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.

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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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Key responsibilities include:

• Building Core Agents & Plays: Design, build, and iterate on the agents and Plays that ship inside our products.
• Owning the Plays Library: Curate and expand our library of pre-built GTM workflows.
• Defining the Marketplace Experience: Own the customer-facing marketplace where users discover, evaluate, and deploy agentic workflows.
• Translating GTM Expertise into Agentic Design: Bring GTM operational expertise to agent design.

To be successful in this role, you will need to have direct experience building agentic workflows, hands-on familiarity with AI-assisted development, and a deep understanding of GTM operations.

If you're a builder first, GTM operations native, and have a strong understanding of agentic workflow intuition, we'd love to hear from you!

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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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The ideal candidate is an Elastic product expert (including but not limited to Agent Builder and Workflows), using the full power of the Elastic Stack to provide the 'brain' and 'memory' for our agentic ecosystem.

As the company behind the popular open-source projects , Elasticsearch, Kibana, Logstash, and Beats , we help people around the world do great things with their data.

The Elastic family unites employees across 40+ countries into one coherent team, while the broader community spans across over 100 countries.

Responsibilities

• Agentic Strategy & Design: Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes.

• Enterprise Grounding: Apply Retrieval Augmented Generation (RAG) and the Elasticsearch Relevance Engine (ESRE) to ensure agents are deeply grounded in enterprise knowledge for high-accuracy task completion.

• AI Model & Tool Integration: Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action.

• Scalable Infrastructure: Firm understanding of cloud-based environments (AWS, Azure, GCP) in order to support the high-concurrency demands of enterprise agents.

• Lifecycle Management: Oversee the training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant.

• Technical Leadership: Act as a domain expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity.

• Documentation: Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes.

• Security: Implement standards for security and data privacy to protect sensitive information and ensure compliance with relevant regulations.

Requirements

• 3-5 years of work experience in a relevant field.

• Minimum 1 year experience building with the Elastic Stack.

• Knowledge of Elasticsearch Relevance Engine (ESRE), Jina AI, and advanced RAG patterns is critical.

• Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation.

• Agentic Frameworks: Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems.

• Expertise in Enterprise Agentic & Workflow Platforms: Deep familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents).

• Market Trend Integration: Proven ability to apply emerging market trends,such as Multi-Agent Orchestration and Model Context Protocol (MCP),to build high-impact, cost-optimized solutions that scale across the enterprise.

• Programming: Experience with Python or TypeScript for backend logic and agent orchestration.

• Cloud & Orchestration: Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment.

• Model Expertise: Hands-on experience with LLM providers.

Bonus Points

• Bachelor’s or Master’s degree in Computer Science or a related engineering field.

• Strong communication skills with the ability to translate business requirements into technical agent architectures.

• A commitment to Ethical AI and responsible development practices.

• Experience with containerization and orchestration (e.g., Docker, Kubernetes).

• Knowledge of DevOps practices for model deployment and automation.

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As the company behind the popular open-source projects , Elasticsearch, Kibana, Logstash, and Beats , we help people around the world do great things with their data. From stock quotes to Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots.

Responsibilities

• Agentic Strategy & Design: Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes.
• Enterprise Grounding: Apply Retrieval Augmented Generation (RAG) and the Elasticsearch Relevance Engine (ESRE) to ensure agents are deeply grounded in enterprise knowledge for high-accuracy task completion.
• AI Model & Tool Integration: Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action.
• Scalable Infrastructure: Firm understanding of cloud-based environments (AWS, Azure, GCP) in order to support the high-concurrency demands of enterprise agents.
• Lifecycle Management: Oversee the training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant.
• Technical Leadership: Act as a domain expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity.
• Documentation: Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes.
• Security: Implement standards for security and data privacy to protect sensitive information and ensure compliance with relevant regulations.

Requirements

• 3-5 years of work experience in a relevant field.
• Minimum 1 year experience building with the Elastic Stack.
• Knowledge of Elasticsearch Relevance Engine (ESRE), Jina AI, and advanced RAG patterns is critical.
• Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation.
• Agentic Frameworks: Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems.
• Expertise in Enterprise Agentic & Workflow Platforms: Deep familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents.)
• Market Trend Integration: Proven ability to apply emerging market trends,such as Multi-Agent Orchestration and Model Context Protocol (MCP),to build high-impact, cost-optimized solutions that scale across the enterprise.
• Programming: Experience with Python or TypeScript for backend logic and agent orchestration.
• Cloud & Orchestration: Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment.
• Model Expertise: Hands-on experience with LLM providers.

Bonus Points

• Bachelor’s or Master’s degree in Computer Science or a related engineering field.
• Strong communication skills with the ability to translate business requirements into technical agent architectures.
• A commitment to Ethical AI and responsible development practices.
• Experience with containerization and orchestration (e.g., Docker, Kubernetes).
• Knowledge of DevOps practices for model deployment and automation.

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Responsibilities

• Lead the end-to-end development of experiential marketing programs that bring Spotify to life across physical, digital, and hybrid environments
• Translate brand strategy into culturally relevant experiences rooted in music, creators, and fandom
• Partner closely with Music, Brand, Content, Partnerships, and Comms teams to align experiences with broader business priorities
• Design and execute live music moments including concerts, showcases, fan events, and listening experiences
• Identify new formats for immersive experiences that blend IRL and digital touchpoints
• Co-create experiences with brand partners while ensuring Spotify's creative integrity remains strong
• Define and track KPIs such as brand lift, engagement, earned media, and fandom growth
• Manage agency partners and vendors to deliver high-quality, innovative execution
• Own planning, budgets, timelines, and risk management for complex programs
• Oversee on-ground execution including production, logistics, talent, and staffing
• Continuously analyse performance and evolve experiential strategy based on insights

Requirements

• 8+ years of experience in experiential marketing, brand marketing, live events, or partnerships
• Led large-scale experiential campaigns or live music events from concept to execution
• Experienced working with artists, creators, agencies, and production partners
• Strong understanding of culture, music, and fandom in India
• Comfortable navigating ambiguity and influencing across cross-functional teams
• Willing to travel and work non-traditional hours around live events

Benefits

• Flexible work arrangements
• Opportunities for professional growth and development
• Collaborative and dynamic work environment
• Access to Spotify's platforms and tools
• Comprehensive benefits package

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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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Location

San Francisco

Employment Type

Full time

Department

Marketing

Compensation

• $284K – $415K

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.

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.

About the team

OpenAI’s mission is to ensure the responsible and widespread adoption of artificial intelligence. In support of that mission, the Marketing team helps deeply understand customer audiences and market dynamics, influence the development of the right products, build sustainable and customer-aligned monetization models, and drive awareness, adoption, and usage across OpenAI’s products and platform.

We take a data-driven approach to understand markets, develop monetization strategies, and uncover customer needs that shape product strategy and messaging. We partner closely with Sales, Partnerships, Product, Engineering, Research, Comms, and Design to deliver a cohesive end-to-end customer experience and lead go-to-market efforts for new product launches across channels.

About the role

We’re looking for a Monetization Product Marketer, Advertising to help shape and scale our advertising products and go-to-market strategy. You’ll combine strategy, market and customer insight with strong product intuition to guide roadmap priorities, mitigate product risks, and deliver launches and coordinate go-to-markets that drive adoption and measurable business impact. This role is ideal for someone who thrives in ambiguity, enjoys turning complex technical capabilities into clear customer value, and can lead cross-functional work in a fast-moving environment.

In this role you will:

• Lead market assessment and customer discovery to identify advertiser needs, market trends, and competitive dynamics

• Translate insights into clear product requirements, positioning, and go-to-market plans in close partnership with Product and Engineering

• Partner with Design, Data Science, and Analytics to define success metrics, measurement strategy, and experimentation plans

• Identify product risk areas (e.g., performance, safety, policy, trust) and drive cross-functional plans to mitigate them

• Own launch strategy and execution for new and improved advertising products, including messaging, enablement, and rollouts

• Build narratives and materials that explain value simply (e.g., positioning, sales decks, one-pagers, FAQs, internal comms)

• Lead the go-to-market strategy and coordination to drive product adoptions and sales in coordination with Sales, Partnerships and Product (Including client communications, product documentation, and positioning)

• Coordinate across stakeholders to keep workstreams aligned, remove blockers, and deliver outcomes on time

• Continuously evaluate and improve existing experiences to drive retention, performance, and advertiser satisfaction

You might be a great fit if you…

• Have strong structured problem solving skills - taking ambiguous problems, breaking them down into answerable parts and then designing and managing a process to answer these questions and driving implementation

• Can connect advertiser needs to product strategy, and influence prioritization across Product/Engineering/Design

• Understand the advertising ecosystem: measurement, targeting/relevance, creative, auctions, and performance tradeoffs

• Have experience marketing products—especially advertising, marketing tech, platforms, or data/AI products

• Communicate clearly and persuasively—turning technical concepts into crisp customer value and differentiated positioning

• Are fluent in both qualitative and quantitative research (customer interviews, surveys, funnel analysis, experimentation)

• Thrive in fast-paced, ambiguous environments and can manage multiple concurrent projects with strong judgment

• Are highly collaborative, proactive, and comfortable leading cross-functional efforts without direct authority

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 artificial intelligence while also ensuring that AI is developed in a way that is safe and beneficial to society.

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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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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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