OpenAI
Machine Learning Engineer, Implicit Signals
San Francisco · Contract
Sponsorship not specifiedDetected 3 days ago
Machine LearningAgentic AIMLOpsStatisticsA/B TestingResearch
Stay score
odds of building a lasting career here
42Risky
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- This role combines traditional machine learning, model evaluation, and real-time engineering.
- You'll work closely with researchers to identify valuable problems and with software engineers to make promising approaches useful at scale.
- We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products.
Responsibilities
- Build, deploy, and operate production classification and evaluation systems that provide useful feedback to post-training and research teams.
- Optimize production inference, including model serving, batching, caching, throughput, latency, compute utilization, and cost.
- Train and optimize classifiers using supervised fine-tuning and distillation, validating quality and efficiency before deployment.
- Own the reliability and observability of deployed classifiers, diagnose production issues, and improve their performance over time.
- Design rigorous evaluations that assess accuracy, calibration, generalization, and potential measurement bias while guiding production tradeoffs.
- Partner with software engineers to integrate models into reliable execution systems and support safe rollouts.
- Build reusable engineering tools that make classifier training, evaluation, deployment, and iteration faster and more repeatable.
- Strong software engineering skills and the ability to build maintainable production ML systems.
Requirements
- The ability to combine careful scientific judgment with a practical approach to shipping and operating software.
Benefits
- Strong foundations in supervised learning, statistics, and experimental design.
Company info
- Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior.
- We work closely with research teams to develop useful measurements and make them practical to run.
- Our work spans classifier development, rigorous evaluation, and efficient production inference, with ownership from initial experimentation through deployment and continued improvement.
- OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.
This listing is sourced directly from OpenAI's careers page and normalized into a canonical job model.