3 months ago
Base Salary
$295k - $445k/yr
Responsibilities
- Design and run experiments to improve scaling of compute on context.
- Own end-to-end improvements to the post-training stack, including reinforcement learning, data pipelines, graders, reward signals, evaluations, diagnostics, and model-behavior analysis.
- Build evaluations and environments that reveal model failures and convert them into training data, product fixes, or research directions.
- Partner with Codex and ChatGPT product teams to translate user needs and product signals into model improvements.
- Develop early-training and alignment interventions involving data mixtures, objectives, synthetic data, and evaluation loops.
- Help determine which integrations, capabilities, and fixes are ready for major model runs.
- Improve large-scale training and launch systems for experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness.
- Debug failures in shipped or near-shipped models and develop concrete hypotheses, experiments, and fixes.
- Work on cross-functional projects involving model training, product infrastructure, production agent harnesses, multi-agent systems, and production-like environments.
Requirements
- Strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field.
- Hands-on experience with LLMs, reinforcement learning, RLHF/RLAIF, post-training, evaluations, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems.
- Ability to translate ambiguous behavioral problems into hypotheses, pipelines, experiments, model runs, analyses, and decisions.
- Comfort working across research, product, infrastructure, data, evaluation, and safety teams.
- Clear communication skills and willingness to build robust systems and processes.
Categories
AI ResearchML Engineering
About OpenAI
OpenAI builds and deploys large-scale AI models and tools—including ChatGPT, GPT-4–class models, DALL·E, and Whisper—sold via APIs and enterprise subscriptions to developers and businesses. It monetizes through usage-based API pricing and ChatGPT Plus/Team/Enterprise, and also reaches customers via Microsoft’s Azure OpenAI Service. Founded in 2015 and headquartered in San Francisco, it operates as a private partnership.