Agent Post-Training, Context Research

Details

The Agent Post-Training team builds the training data, environments, graders, training methods, and feedback loops that shape OpenAI's frontier agents (Codex, ChatGPT, the API, and other products). This role focuses on scaling compute spent on context and improving post-training systems to enable the next paradigm of model training (including work on Codex Chronicle). You will work cross-functionally with researchers, engineers, product, infrastructure, and safety/alignment partners to decide what goes into major model runs, measure outcomes, and ship improvements to production.

Responsibilities

• Design and run experiments that improve scaling of compute on context.
• Own end-to-end improvements to the post-training stack: RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis.
• Build evals and environments that expose model failures and turn failures into training data, product fixes, or new research directions.
• Partner with Codex and ChatGPT product teams to translate product signal into model improvements.
• Work on early-training and alignment interventions: data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior.
• Decide which integrations, capabilities, and fixes are ready for inclusion in major model runs.
• Improve experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness for large-scale training and launches.
• Lead cross-functional projects touching model training, product infrastructure, and production agent harness (e.g., multi-agent systems or training against production-like environments).
• Debug hard failures in shipped or near-shipped models and convert qualitative behavior into concrete hypotheses, experiments, and fixes.

Requirements

• Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, with the ability to learn quickly across unfamiliar areas.
• Hands-on experience with large language models (LLMs), reinforcement learning (RL), RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.
• Ability to move from a vague behavioral problem to a concrete experiment: define hypotheses, build pipelines, run models, analyze results, and decide next steps.
• Comfortable working across research, product, infrastructure, data, evals, and safety boundaries and communicating clearly with each group.
• Interest in product impact and model behavior (reliability, factuality, instruction-following, calibrated reasoning, and taste).
• Appetite for open-ended problems where the path is unclear and signal is noisy; willingness to build load-bearing systems and processes when needed.

About OpenAI

OpenAI is an AI research and deployment company focused on ensuring general-purpose AI benefits all of humanity. The posting includes standard equal employment and affirmative action statements and notes background checks will be administered in accordance with applicable law. OpenAI provides reasonable accommodations to applicants with disabilities.

Benefits

• Estimated base salary range: $295,000 — $445,000 (base pay may vary by location, experience, and other factors). Total compensation may include equity and performance-related bonuses.
• Medical, dental, and vision insurance with employer contributions to Health Savings Accounts.
• Pre-tax accounts: 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; up to 20 weeks for non-birthing parents) and paid medical/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 coordinated company office closures; paid sick or safe time as required by law.
• Mental health and wellness support; employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily meals in offices and meal delivery credits as eligible.
• Relocation support for eligible employees.
• Additional taxable fringe benefits (e.g., charitable donation matching, wellness stipends).