You'll be hands-on: write specs, prototype solutions, dig into technical architecture with engineers, and make product calls grounded in real technical understanding. You'll design and ship AI-powered products and tooling for defense and national security workflows, working side-by-side with engineering and ML teams.

You'll use customer context to inform what you build , understand allied defense workflows deeply enough to make opinionated product decisions, not just relay requirements. You'll navigate the unique constraints of defense product development across allied nations , classification environments, accreditation processes, air-gapped deployments , or be ready to learn these fast.

Ideally, you'd have a builder mentality: you're energized by going from zero to one, not by managing from a distance. You'll have 8+ years of experience in software engineering, ML engineering, or a deeply technical product role where you were hands-on with what shipped. You'll have technical fluency: software engineering or ML background (master's degree in computer science or equivalent experience).

Please note that our policy requires a 90-day waiting period before reconsidering candidates for the same role.

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Key responsibilities include:

• Owning the creation of model evaluation from initial hypothesis, data scraping to final publication.
• Deeply analysing why the model failed and identifying semantic patterns, edge cases, and systemic hallucinations in raw model outputs.
• Reviewing raw data sets, meeting transcripts, and research notes to identify the 'so what' and turning these findings into a logical hierarchy.
• Acting as the bridge between the data and the narrative by structuring findings into a logical hierarchy where the most critical 'hook' lands first, followed by the supporting evidence.

As a successful candidate, you will have 5-10 years of experience in DS, ML, AI research and analysis, be a structured thinker, have a high tolerance for ambiguity, and possess executive presence. Experience in Model Evaluation, ML Engineering or Technical Research is a plus.

This role offers a competitive compensation package, including base salary, equity, and benefits. The base salary range for this full-time position in San Francisco is $205,600-$257,000 USD.

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The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.

Key responsibilities include:

• Contributing to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
• Designing and developing ML and Generative AI systems in cloud-based production environments at scale.
• Building and managing enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
• Implementing and operationalizing agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
• Driving adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
• Establishing best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.

The ideal candidate will have:

• 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Experience operating orchestration systems such as Kubernetes at scale.
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more.
• Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders.
• Strong focus on scalability, reliability, performance, and ease of use.

Benefits include comprehensive healthcare benefits, income replacement programs, 401k with employer match, global benefit programs, family planning support, gender-affirming care, mental health & coaching benefits, flexible vacation & paid volunteer time off, and generous paid parental leave.

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Our team is responsible for adopting Generative AI technologies to enable an intelligent, scalable, and exceptional service experience. We work closely with product, design, and other engineering counterparts to design and build efficient AI solutions for Airbnb's CS products.

As a Staff Machine Learning Engineer, you will have the opportunity to shape the direction of our AI initiatives and work on cutting-edge projects that transform Airbnb's customer service. You will be responsible for envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.

Requirements:

• PhD/Master's degree in Computer Science or equivalent experience
• 6/9+ years of ML engineering experience with ownership responsibility over large-scale software systems
• Background in the design and development of AI and ML systems and services
• Experience with LLM driven chatbot and Agentic AI products is a plus
• Excellent communication skills and the ability to work well within a team and with teams across the engineering, product & design organizations

Our Commitment to Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services, and solutions. All qualified individuals are encouraged to apply.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs, and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range: $204,000-$255,000 USD

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As a member of Medium’s Machine Learning & Insights team, you’ll partner closely with stakeholders across teams to help deepen our collective understanding of Medium’s members, writers, and business through data.

You'll work alongside our Principal Scientist, contributing methodological rigor to strategic initiatives while owning end-to-end research and model development in your domain.

This is a unique role for someone with a track record of solving big, ambiguous problems at the intersection of data, product, and business strategy.

You’ll do more than ivory-tower modeling; you’ll help us define what “content quality” looks like, design better experiments, and ship real product changes to users.

If you love both statistical rigor and real-world business impact, this might be the role for you!

Key Responsibilities

• Proactively identify valuable areas of investigation that help deepen our understanding of our members, writers, and overall business.

• Partner with diverse technical and non-technical stakeholders across the company to develop hypotheses and generate actionable insights in their domains.

• Work with executives at Medium, including our CEO, to model and present data insights and findings.

• Build and maintain statistical and predictive models about Medium’s business.

• Run research projects and investigations, small and large, for leadership and cross-functional partners.

• Develop and maintain quantitative models that support forecasting and strategic planning.

• Share knowledge with and mentor engineers and other stakeholders to improve their own analytics capabilities.

• Contribute to the broader data culture and ecosystem at Medium, helping to raise our data fluency as a team.

• Attend Medium’s twice-yearly, in-person offsites (hosted in locations around the U.S.).

Skills, Knowledge and Expertise

• You know your way around data. You have 4-6 years of experience as an in-house data scientist, with a proven track record of driving business impact through data.

• You're highly proficient in statistical programming with either Python or R, and you’re comfortable writing SQL for analytical queries. (Python skills are strongly preferred. Our team uses Python extensively, and we’ll be expecting candidates to demonstrate Python scripting skills during the interview process.)

• You have a track record of building, validating, and deploying predictive and statistical models that drove measurable business outcomes.

• You're a strong collaborator with an established history of cross-team and executive-level partnership.

• You care about quality writing, informed readership, and building a sustainable model for creators. Experience applying modeling techniques to problems unique to social platforms, subscription/membership businesses, or publishing is a plus.

• Experience with ML engineering practices, dbt, or data engineering is a plus! We're a small team, and the folks who do best are those who like to wear many hats.

Benefits

In addition to the new skills you'll pick up, here's what else you'll enjoy by working at Medium:

• Working with a fully distributed team: We’re fully remote and have teammates across the U.S. & France.

• Healthcare benefits covered at 100% for employees and 70% for dependents.

• Generous parental leave policy.

• Mental health support through Talkspace.

• Financial wellness support through Northstar.

• Stipends for co-working, professional development, wifi, and a one-time home office bonus.

• Unlimited PTO and standard company holidays.

• A discounted Medium membership!

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This is a role that sits at the intersection of product thinking, service design, and cross-functional influence. You will design, manage, and enable the services that move customers forward at every stage of that journey.

Your responsibilities will include:

• Owning the end-to-end service portfolio for your assigned product area , offer design, pricing, BOM standards, lifecycle management, field enablement, and sunset decisions
• Mapping and continuously refining the complete customer journey for your product area, defining how customers are guided across scaled digital motions, Customer Success Tiers, Professional Services, and Education and Training
• Defining measurable customer outcomes and value anchors for each offering, ensuring every service can clearly articulate what success looks like and how it is verified
• Acting as product manager for your product area tooling requirements into the CX Engineering Platform team , writing requirements, reviewing prototypes, managing a backlog, and conducting UAT
• Partnering with PS Engineers, Customer Success, Project Managers, and Solution Architects to gather field input and translate it into refined or net-new service offerings
• Building and maintaining relationships with stakeholders across the full organizational range , from PSEs and CSMs who deliver your services in the field, through to VP-level PS and CS leadership and C-suite executives
• Collaborating with your peers across the CX Services Portfolio team to design consistent customer experiences and ensure services are properly sequenced across the customer lifecycle
• Creating and maintaining field enablement materials , playbooks, objection handling guides, Highspot pages, talk tracks, and training sessions , for CSMs, CSAs, PSEs, and AEs
• Using AI tools actively in your daily workflow to accelerate research, drafting, synthesis, and requirement writing , and contributing what you learn to the team shared AI practice

To succeed in this role, you will need:

• 7+ years of experience in professional services, customer success, solutions architecture, or product management at a SaaS company
• Demonstrated experience designing or managing service offerings , not just delivering them. You have written a scope of work, defined pricing, and built a delivery kit
• Strong understanding of DevOps, application development, SDLC, or security domains , you do not need GitLab product knowledge on day one, but you need the technical foundation to develop it quickly
• Technical depth sufficient to design credible services. You do not need to have delivered these engagements yourself, but you need to understand them well enough that the practitioners who do will trust your judgment
• Deep familiarity with AI/ML engineering workflows, LLM capabilities, and agentic systems , and the organizational change management required for enterprise AI adoption
• A demonstrated AI-forward working style , you actively use agentic coding and AI tools as part of your daily workflow. You have formed opinions about how these tools change the way you work, and you can walk us through a specific workflow you have built or discovered that materially changed your output quality or speed
• Proven ability to build trust and communicate effectively across the full stakeholder range , individual contributors, managers, directors, VPs, and C-suite , in a remote, async-first environment
• Commercial acumen: fluency in how professional services and subscription services are priced, packaged, and sold in an enterprise context
• Strong written communication skills: you can produce clear, concise, and compelling content that resonates with diverse audiences

If you're passionate about designing and delivering exceptional customer experiences, and you have a strong background in professional services, customer success, or product management, we encourage you to apply for this exciting opportunity.

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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 company with a diverse workforce and teams distributed between France, USA, UK, Germany and Singapore. We are looking for passionate and skilled software engineers to join our team.

Role Summary

We are seeking passionate and skilled software engineers to join our team. As a Backend Engineer, you’ll contribute to the development of the core systems powering our three main products, AI Studio, Le Chat & Mistral Code, shaping how users and developers interact with our AI platform at scale.

Responsibilities

Depending on your skills and field of expertise, you will be involved in key components of our technology, including:

• Backend Development - Design, develop and maintain scalable, robust backend features and APIs using modern frameworks.
• Ensure high performance and reliability across our distributed systems.
• Contribute to systems powering authentication, billing, AI tooling, observability, connectors, and developer experience.

System Architecture

• Design and implement efficient, secure and scalable architectures that support our fast-growing products.
• Collaborate with infrastructure teams on deployment, monitoring, and performance optimization.

Code Quality

• Write clean, maintainable and well-documented code.
• Participate in code reviews and contribute to technical standards and best practices.

Cross-functional Collaboration

• Work closely with product managers, front-end engineers, designers and data/AI engineers to deliver end-to-end features.
• Partner with teams across AI Studio, Le Chat & Mistral Code to ensure consistent platform-wide experience.

Problem-Solving & Innovation

• Tackle complex engineering challenges, from distributed systems to AI product integration.
• Stay up-to-date with new technologies (e.g., AI/LLM integration, observability, or backend frameworks) and bring them into production when relevant.

About You

• Degree in Computer Science, Software Engineering, or equivalent practical experience.
• Proficiency in Python or another backend language (JavaScript/TypeScript, C#, Golang).
• Strong understanding of backend fundamentals: APIs, databases, caching, messaging systems and distributed architectures.
• Strong problem-solving abilities and attention to detail.
• Ownership mindset capable of shipping end-to-end features with minimal oversight.
• Excellent communication skills and collaborative attitude.

Experience Level

This role is suitable for entry-level, mid-level, senior-level, and staff-level engineers.

Employment Type

This is a full-time position.

Workplace Type

This role is based in one of our European offices (Paris, France and London, UK).

Category

This role falls under the category of Engineering.

Industry

This role is in the Technology industry.

Salary Range

The salary range for this position is competitive and will be discussed during the hiring process.

Required Skills

• Python
• Backend development
• APIs
• Databases
• Caching
• Messaging systems
• Distributed architectures

Preferred Skills

• Front-end development
• Infrastructure management
• AI/ML engineering
• Observability and monitoring tools
• UX and product-centric mindset

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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. We are a low-ego and team-spirited organisation.

Role Summary

We are seeking passionate and skilled software engineers to join our team. As a Backend Engineer, you’ll contribute to the development of the core systems powering our three main products, AI Studio, Le Chat & Mistral Code, shaping how users and developers interact with our AI platform at scale.

Responsibilities

Depending on your skills and field of expertise, you will be involved in key components of our technology, including:

• Backend Development: Design, develop and maintain scalable, robust backend features and APIs using modern frameworks. Ensure high performance and reliability across our distributed systems. Contribute to systems powering authentication, billing, AI tooling, observability, connectors, and developer experience.

• System Architecture: Design and implement efficient, secure and scalable architectures that support our fast-growing products. Collaborate with infrastructure teams on deployment, monitoring, and performance optimisation.

• Code Quality: Write clean, maintainable and well-documented code. Participate in code reviews and contribute to technical standards and best practices.

• Cross-functional Collaboration: Work closely with product managers, front-end engineers, designers and data/AI engineers to deliver end-to-end features. Partner with teams across AI Studio, Le Chat & Mistral Code to ensure consistent platform-wide experience.

• Problem-Solving & Innovation: Tackle complex engineering challenges, from distributed systems to AI product integration. Stay up-to-date with new technologies (e.g., AI/LLM integration, observability, or backend frameworks) and bring them into production when relevant.

About You

• Degree in Computer Science, Software Engineering, or equivalent practical experience.
• Proficiency in Python or another backend language (JavaScript/TypeScript, C#, Golang).
• Strong understanding of backend fundamentals: APIs, databases, caching, messaging systems and distributed architectures.
• Strong problem-solving abilities and attention to detail.
• Ownership mindset capable of shipping end-to-end features with minimal oversight.
• Excellent communication skills and collaborative attitude.

Now, it would be ideal if you had experience with:

• Front-end development (Typescript, React, NextJS...)
• Infrastructure management (Docker, CI/CD, Kubernetes, Helm, Terraform...)
• AI/ML engineering
• Observability and monitoring tools (Prometheus, Grafana, Datadog…)
• UX and product-centric mindset.

Hiring Process

• Introduction call - 45 minutes
• Live-coding interview - 45 minutes
• System Design interview - 45 minutes
• Hiring Manager interview - 30 minutes
• Deep Dive Interview (only for leads & staff engineers) - 60 minutes
• Culture-fit discussion - 30 minutes
• Reference checks

Our Culture

We're driven to build a strong company culture and are looking for individuals with solid alignment with the following:

• Reason with rigor
• Are you audacious enough?
• Make our customers succeed
• Ship early and accelerate
• Leave your ego aside

Engineering blog

Our first Engineering blog post is live, you can check it out here!

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Reporting line: VP of Engineering

Location: Paris (France) or London (UK)

Key Responsibilities: The Knowledge & Search team is the backbone that connects our customers to the information they need. We are looking for an experienced software engineer to lead our indexing and searching capabilities. In this role, you will work closely with our data and infrastructure teams to build, maintain and scale our search platform while ensuring a high-level of performance and reliability.

Your responsibilities include (but may not be limited to):

• Building, maintaining and enhancing a fast, reliable and scalable indexing and searching capabilities (web and knowledge)

• Working with search-oriented databases to optimise and fine-tune full search pipelines from document ingestion to retrieval

• Owning our information retrieval systems serving both our internal needs as well as our enterprise customers

• Ensuring that our search capabilities meet the increasing demands of our customers

• Collaborate with internal and external stakeholders to push the boundaries of search reliability, performance, and scale across a range and cloud-native and on-premise services.

About you:

• 7+ years of relevant professional work experience

• Master’s degree in Computer Science, Information Technology or a related field

• Experience building and scaling distributed search engine systems

• Excellent proficiency in backend software development (Python, Go, C++, Rust...)

• Solid proficiency in infrastructure management (Docker, CI/CD, Helm, K8s, Terraform...)

• Good knowledge of cloud-native ecosystems

• Autonomous and self-starter

• Ability to communicate with influence

Now, it would be ideal if you had experience with:

• AI/ML engineering

Hiring Process:

Here is what you should expect:

• Introduction call - 30 min

• Hiring Manager Interview - 30 min

• Live-coding Interview (Python) - 45 min

• System Design Interview - 45 min

• Optional: Deep Dive Interview (Staff/Lead specific) - 60 min

• Culture-fit discussion - 30 min

• References

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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 pioneering company shaping the future of AI. Our comprehensive AI platform meets enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.

Role Summary

We are seeking passionate and skilled software engineers to join our team. As a Backend Engineer, you’ll contribute to the development of the core systems powering our three main products, AI Studio, Le Chat & Mistral Code, shaping how users and developers interact with our AI platform at scale.

Responsibilities

Depending on your skills and field of expertise, you will be involved in key components of our technology, including:

• Backend Development: Design, develop and maintain scalable, robust backend features and APIs using modern frameworks. Ensure high performance and reliability across our distributed systems. Contribute to systems powering authentication, billing, AI tooling, observability, connectors, and developer experience.

• System Architecture: Design and implement efficient, secure and scalable architectures that support our fast-growing products. Collaborate with infrastructure teams on deployment, monitoring, and performance optimization.

• Code Quality: Write clean, maintainable and well-documented code. Participate in code reviews and contribute to technical standards and best practices.

• Cross-functional Collaboration: Work closely with product managers, front-end engineers, designers and data/AI engineers to deliver end-to-end features. Partner with teams across AI Studio, Le Chat & Mistral Code to ensure consistent platform-wide experience.

• Problem-Solving & Innovation: Tackle complex engineering challenges, from distributed systems to AI product integration. Stay up-to-date with new technologies (e.g., AI/LLM integration, observability, or backend frameworks) and bring them into production when relevant.

About You

• Degree in Computer Science, Software Engineering, or equivalent practical experience.
• Proficiency in Python or another backend language (JavaScript/TypeScript, C#, Golang).
• Strong understanding of backend fundamentals: APIs, databases, caching, messaging systems and distributed architectures.
• Strong problem-solving abilities and attention to detail.
• Ownership mindset capable of shipping end-to-end features with minimal oversight.
• Excellent communication skills and collaborative attitude.

Now, it would be ideal if you had experience with:

• Front-end development (Typescript, React, NextJS...)
• Infrastructure management (Docker, CI/CD, Kubernetes, Helm, Terraform...)
• AI/ML engineering
• Observability and monitoring tools (Prometheus, Grafana, Datadog…)
• UX and product-centric mindset.

Hiring Process

• Introduction call - 45 min
• Live-coding interview - 45 min
• System Design interview - 45 min
• Hiring Manager interview - 30 min
• Deep Dive Interview (only for leads & staff engineers) - 60 min
• Culture-fit discussion - 30 min
• Reference checks

Our Culture

We're driven to build a strong company culture and are looking for individuals with solid alignment with the following:

• Reason with rigor
• Are you audacious enough?
• Make our customers succeed
• Ship early and accelerate
• Leave your ego aside

Engineering blog

Our first Engineering blog post is live, you can check it out here!

XML job scraping automation by YubHub

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 organisation with a diverse workforce distributed between France, USA, UK, Germany, and Singapore. Our teams are passionate about AI and its potential to transform society.

Role Summary

We are seeking passionate and skilled software engineers to join our team. As a Backend Engineer, you'll contribute to the development of the core systems powering our three main products, AI Studio, Le Chat & Mistral Code, shaping how users and developers interact with our AI platform at scale.

Responsibilities

Depending on your skills and field of expertise, you will be involved in key components of our technology, including:

• Backend Development: Design, develop, and maintain scalable, robust backend features and APIs using modern frameworks. Ensure high performance and reliability across our distributed systems. Contribute to systems powering authentication, billing, AI tooling, observability, connectors, and developer experience.

• System Architecture: Design and implement efficient, secure, and scalable architectures that support our fast-growing products. Collaborate with infrastructure teams on deployment, monitoring, and performance optimisation.

• Code Quality: Write clean, maintainable, and well-documented code. Participate in code reviews and contribute to technical standards and best practices.

• Cross-functional Collaboration: Work closely with product managers, front-end engineers, designers, and data/AI engineers to deliver end-to-end features. Partner with teams across AI Studio, Le Chat & Mistral Code to ensure consistent platform-wide experience.

• Problem-Solving & Innovation: Tackle complex engineering challenges, from distributed systems to AI product integration. Stay up-to-date with new technologies (e.g., AI/LLM integration, observability, or backend frameworks) and bring them into production when relevant.

About You

• Degree in Computer Science, Software Engineering, or equivalent practical experience.
• Proficiency in Python or another backend language (JavaScript/TypeScript, C#, Golang).
• Strong understanding of backend fundamentals: APIs, databases, caching, messaging systems, and distributed architectures.
• Strong problem-solving abilities and attention to detail.
• Ownership mindset capable of shipping end-to-end features with minimal oversight.
• Excellent communication skills and collaborative attitude.
• Team-oriented, low-ego mindset, and curiosity for learning.

Now, it would be ideal if you had experience with:

• Front-end development (Typescript, React, NextJS...)
• Infrastructure management (Docker, CI/CD, Kubernetes, Helm, Terraform...)
• AI/ML engineering
• Observability and monitoring tools (Prometheus, Grafana, Datadog…)
• UX and product-centric mindset.

Hiring Process

• Introduction call - 45 minutes
• Live-coding interview - 45 minutes
• System Design interview - 45 minutes
• Hiring Manager interview - 30 minutes
• Deep Dive Interview (only for leads & staff engineers) - 60 minutes
• Culture-fit discussion - 30 minutes
• Reference checks

Our Culture

We're driven to build a strong company culture and are looking for individuals with solid alignment with the following:

• Reason with rigor
• Are you audacious enough?
• Make our customers succeed
• Ship early and accelerate
• Leave your ego aside

Engineering blog

Our first Engineering blog post is live, you can check it out here!

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The Hugging Face ML Cloud team is working through strategic collaborations with the most used Clouds (AWS, GCP, Azure, Cloudflare), AI Accelerators (incl. NVIDIA, AMD, Intel, Gaudi, Inferentia, TPU), and Systems (Dell, Nutanix), to make it easy for the community to use Hugging Face models and libraries on these compute platforms.

This role is not a marketing role, or a business development role. Your impact will be driving visibility and usage of integrations with strategic partners, through activities including:

• Publishing technical blog posts
• Contributing documentation and code examples
• Speaking to business and technical audiences at partner conferences,
• Participating in, or producing webinars
• Building and evangelizing demos
• Leading GTM conversations with strategic partners.

You will be at the forefront of Generative AI (and how to build practical stuff with open source). You will work hand in hand with the most important companies in AI. You will enjoy a lot of autonomy and full creative control, with the goal to have 10x more impact than a similar role at a big tech corporation.

About You

You are passionate about ML Engineering, building practical AI applications, putting them in production, and accelerating them to the best of the Cloud ability. You love learning new challenging engineering concepts and technologies, and discussing them with engineers. You appreciate a good Developer Experience, and take pride in your code being easy to understand. You are a great communicator and educator, comfortable (as much as one can be!) with public speaking to technical audiences. You love engaging with the ML community in a positive and helpful way. Existing engagement in social platforms (GitHub, LinkedIn, Twitter, Reddit, etc) or other communication/education channels is expected. Having experience in Open Source development will be helpful.

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The Knowledge & Search team is the backbone that connects our customers to the information they need. We are looking for an experienced software engineer to lead our indexing and searching capabilities. In this role, you will work closely with our data and infrastructure teams to build, maintain and scale our search platform while ensuring a high-level of performance and reliability.

Key Responsibilities:

• Building, maintaining and enhancing a fast, reliable and scalable indexing and searching capabilities (web and knowledge)
• Working with search-oriented databases to optimise and fine-tune full search pipelines from document ingestion to retrieval
• Owning our information retrieval systems serving both our internal needs as well as our enterprise customers
• Ensuring that our search capabilities meet the increasing demands of our customers
• Collaborate with internal and external stakeholders to push the boundaries of search reliability, performance, and scale across a range and cloud-native and on-premise services.

About you:

• 7+ years of relevant professional work experience
• Master’s degree in Computer Science, Information Technology or a related field
• Experience building and scaling distributed search engine systems
• Excellent proficiency in backend software development (Python, Go, C++, Rust...)
• Solid proficiency in infrastructure management (Docker, CI/CD, Helm, K8s, Terraform...)
• Good knowledge of cloud-native ecosystems
• Autonomous and self-starter
• Ability to communicate with influence

Now, it would be ideal if you had experience with:

• AI/ML engineering

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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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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.

About the team

OpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and durable products.

About the role

Platform Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.

You will partner with customer-tagged FDEs who are driving delivery and customer outcomes, and embed where you can provide the highest leverage. In practice that means working in the trenches on architecture, product shaping, refactoring, hardening, and reusable abstractions, while preserving the pod’s ownership of customer understanding and day-to-day execution. You will also collaborate closely with our B2B Platform Team and other long-term owners to align early on what should generalize, what should remain customer-specific, and what “ready for handoff” looks like.

This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically <0%, with occasional spikes for key embeds or launches.

In this role you will

• Provide hands-on leverage to customer pods: embed with customer-tagged FDE teams to support generalization, contributing directly in architecture, product shaping, refactoring, and implementation.

• Turn repeated signals into platform bets: translate cross-customer patterns into crisp hypotheses with clear success criteria, scope, and a validation plan that fits real account constraints.

• Raise the engineering bar through tooling and mentorship: set org-wide quality norms through high-signal code review and pairing, and build lightweight developer tooling that makes good architecture, readability, and correctness the default across FDE.

• Collaborate as part of cross-functional platform teams: partner closely with B2B Product, customer-tagged FDEs, ops, and business partners to bring the right products and platform capabilities to market.

• Lead complex platform capabilities end-to-end when needed: for high-leverage primitives like our Context Platform, act as DRI from requirements through implementation, make key tradeoffs explicit, and pull in customer pods early to keep the work grounded in real deployments.

You might thrive in this role if you

• Bring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.

• Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).

• Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).

• Communicate clearly across engineering, product, go-to-market, and executive audiences, simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation.

• Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable product requirements and reusable platform capabilities, not one-off fixes or bespoke delivery work.

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.

Experience

5+ years of software engineering or ML engineering experience

Employment Type

Full-time

Workplace Type

Hybrid

Category

Engineering

Industry

Technology

Salary Range

$230K – $385K

Required Skills

• Software engineering
• ML engineering
• Architecture
• Product shaping
• Refactoring
• Hardening
• Reusable abstractions
• Systems thinking

Preferred Skills

• Experience in high-ambiguity, fast-iteration environments
• Customer-adjacent technical work
• Reliability, security, and governance
• Communication across engineering, product, go-to-market, and executive audiences

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Platform Engineer, Forward Deployed Engineering (FDE) - NYC

Location

New York City

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

Compensation

• $230K – $385K

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’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and durable products.

The FDE Platform team is primarily a leverage function that scales the FDE org’s impact to OpenAI’s platform and products. We provide hands-on leverage by embedding with customer-tagged FDE pods to aid in architecting, product shaping, refactoring, and building. This team is perfect for highly collaborative software engineers who love innovating on cutting-edge products with other builders.

About the role

Platform Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.

You will partner with customer-tagged FDEs who are driving delivery and customer outcomes, and embed where you can provide the highest leverage. In practice that means working in the trenches on architecture, product shaping, refactoring, hardening, and reusable abstractions, while preserving the pod’s ownership of customer understanding and day-to-day execution. You will also collaborate closely with our B2B Platform Team and other long-term owners to align early on what should generalize, what should remain customer-specific, and what “ready for handoff” looks like.

This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically <%, with occasional spikes for key embeds or launches.

In this role you will

• Provide hands-on leverage to customer pods: embed with customer-tagged FDE teams to support generalization, contributing directly in architecture, product shaping, refactoring, and implementation.

• Turn repeated signals into platform bets: translate cross-customer patterns into crisp hypotheses with clear success criteria, scope, and a validation plan that fits real account constraints.

• Raise the engineering bar through tooling and mentorship: set org-wide quality norms through high-signal code review and pairing, and build lightweight developer tooling that makes good architecture, readability, and correctness the default across FDE.

• Collaborate as part of cross-functional platform teams: partner closely with B2B Product, customer-tagged FDEs, ops, and business partners to bring the right products and platform capabilities to market.

• Lead complex platform capabilities end-to-end when needed: for high-leverage primitives like our Context Platform, act as DRI from requirements through implementation, make key tradeoffs explicit, and pull in customer pods early to keep the work grounded in real deployments.

You might thrive in this role if you

• Bring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.

• Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).

• Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).

• Communicate clearly across engineering, product, go-to-market, and customer-facing teams to drive alignment and shared understanding of customer needs and technical tradeoffs.

XML job scraping automation by YubHub

Location

New York City

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

Compensation

• $198K – $335K • 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.

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 Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in NYC. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and process improvements.

What we offer

• Competitive salary and equity package

• Opportunity to work with a talented team of engineers and researchers

• Collaborative and dynamic work environment

• Professional development and growth opportunities

• Flexible work arrangements

• Comprehensive benefits package

• Access to cutting-edge technology and resources

How to apply

If you are a motivated and talented individual who is passionate about AI and life sciences, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter explaining why you are a strong fit for this role.

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Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

Compensation

• $198K – $335K • 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.

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 Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

Responsibilities

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

Requirements

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validat

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Location

Paris, France

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in Paris. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

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 / Research Scientist, Post-Training

Location

San Francisco

Employment Type

Full time

Department

Research

Compensation

• $295K – $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

The Post-Training team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable.

About the Role

As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products.

We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research.

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:

• Own and pursue a research agenda to improve model capability and performance.

• Collaborate closely with the other research and product teams, allowing customers to optimize their own models.

• Build robust evaluations for tracking modeling improvements.

• Design, implement, test, and debug code across our research stack.

You might thrive in this role if you:

• Have a deep understanding of machine learning and machine learning applications.

• Have a working knowledge of relevant models, and building evaluations for model capability improvement.

• Are comfortable diving into a large ML codebase to debug.

• Thrive in a dynamic and technically complex environment.

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.

XML job scraping automation by YubHub

Location

London, UK

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in London. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

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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Location

Dublin, Ireland

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in Dublin. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

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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Location

Munich, Germany

Employment Type

Full time

Location Type

Hybrid

Department

Model Deployment for Business

About the team

OpenAI’s Forward Deployed Engineering team partners with global pharma and biotech, CROs, and research institutions to deploy existing expertise across the R&D value chain to help customers design and ship production-grade AI systems. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments.

About the role

We are hiring a Forward Deployed Engineer (FDE) to push the frontier on what is possible today across drug discovery (e.g., target identification, molecular design, pre-clinical) and development (e.g., trial design, trial ops, biostats) by leading end-to-end deployments of our models inside life sciences organizations and research institutions. You will work with customers who are deep experts in their scientific or operational domains, translating real-world data, infrastructure, and constraints into production systems.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback loops, including evaluation benchmarks and acceptance criteria, that inform product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM to deliver in regulated contexts, including inspection readiness with audit trails and traceable evidence.

This role is based in Munich. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows.

• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints.

• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact.

• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling.

• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes.

• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments.

You might thrive in this role if you

• Bring 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software; PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged.

• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation that tightens acceptance criteria over time.

• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout.

• Communicate clearly across scientific, clinical, model research, technical, and executive audiences, translating technical tradeoffs into decision quality, risk posture, and measurable outcomes with credibility.

• Apply systems thinking with high execution standards, consistently turning failures, escalations, and audit findings into improved operating standards, validation artifacts, and repeatable deployment playbooks.

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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