Estimated Base Salary $295K – $445K

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.

Team Description

OpenAI is looking for exceptional researchers to join the Post-Training Frontiers team, which is responsible for post-training the agentic models we ship across Codex, the API, ChatGPT Thinking, and ChatGPT Pro. The Post-Training Frontiers team sets up the pipeline for deciding which integrations can go into the post-training run, develops its own horizontal improvements to the model, and trains the final model.

Responsibilities

• Own end-to-end research and engineering projects that improve the final post-training of OpenAI’s agentic models.

• Decide, together with partner teams, which integrations are ready for inclusion in major model runs.

• Develop horizontal model improvements across factuality, instruction following, tool/function calling, multi-agent behavior, reasoning-effort calibration, and other broad capabilities.

• Build and improve training, evaluation, grading, and data infrastructure for large-scale RL/post-training runs.

• Create evals and diagnostics that help us understand whether a model is ready to ship.

• Improve the feedback loop from real product usage into post-training, including better ways to learn from implicit user feedback.

• Collaborate closely with Codex, API, ChatGPT, product, training, and other post-training teams to make frontier models more useful, reliable, and agentic.

Nice to have

• Experience with large-scale model training or RL systems.

• Experience building evals, graders, reward models, or data pipelines for LLM training.

• Experience with coding agents, tool-using agents, browser/computer-use agents, function calling, or multi-agent systems.

• Background in quant, systems, infra, or other environments where you built reliable machinery for high-stakes experimentation.

• Evidence of strong product taste, especially around writing, design, code generation, or agent workflows.

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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As a Software Engineer on Anthropic's Human Data Interfaces team, you'll own the architecture and execution of our data collection pipelines, designing systems that are both performant at scale and resilient to the rapidly changing needs of our research teams.

Responsibilities

• Architect and build data collection pipelines that support rapid iteration, balancing data quality and system maintainability
• Think deeply about the experience of the crowdworkers and vendors using these systems, building interfaces that are clear, efficient, and lead to high-quality data
• Collaborate closely with research teams to understand evolving data needs and iterate quickly on collection methods
• Partner with our Human Data Operations team to understand the end-to-end data workflow and design interfaces that make their jobs easier
• Prioritize and juggle multiple workstreams, making trade-off decisions in a fast-moving environment where research priorities can shift quickly

You May Be a Good Fit If You:

• Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well
• Are a strong full-stack engineer with broad experience across the stack
• Are very good at building internal tools, including working with users of the tools to understand their needs
• Thrive in fast-moving environments where you need to balance speed of iteration with long-term system health
• Are a quick study,this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level) to be effective

Strong Candidates May Also Have:

• Experience building human data labelling interfaces, human-in-the-loop systems, or data collection pipelines
• Familiarity with how preference data and reward models are used in AI model training
• Experience working with researchers who are internal users/customers
• Background in building, and improving the user-experience of user-facing applications, particularly those involving complex UI interactions or annotation workflows
• Strong instincts around system design , building things that evolve gracefully as requirements change
• Experience influencing technical and product direction on a team

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues

How to Apply

If you're interested in this role, please submit your application through our website. We look forward to hearing from you!

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