# Agent Post-Training, Artifacts Research **Company**: OpenAI **Location**: San Francisco **Experience**: senior **Job type**: Full time **Salary**: $295K - $445K **Category**: Research **Industry**: Technology **Wikidata**: https://www.wikidata.org/wiki/Q124605186 **Apply**: https://jobs.ashbyhq.com/openai/6897d024-88c1-43ed-adb8-5d2fc5eec984?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_5eb05828-829 ## Description We are seeking an Agent Post-Training, Artifacts Research to join our Research team in San Francisco. The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The estimated base salary for this role is $295K – $445K. ## About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. ## About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. ## Responsibilities - Design and run experiments that improve agentic model behavior for complex software and plugins. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. ## 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. - 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. ## Requirements - Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field. - Hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Experience with designing and running experiments, and analyzing results. - Ability to work across research, product, infrastructure, data, evals, and safety boundaries. ## Skills ### Required - machine learning - software engineering - systems - statistics - LLMs - RL - RLHF/RLAIF - post-training - evals - graders - synthetic data - model training --- Source: [Apply at jobs.ashbyhq.com](https://jobs.ashbyhq.com/openai/6897d024-88c1-43ed-adb8-5d2fc5eec984?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)