ML Engineer: Implicit Signals & Production Evaluation

OpenAI, Inc.; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

OpenAI is seeking a machine learning engineer to develop and deploy classification and evaluation capabilities. You will turn open-ended questions about model behavior into ML problems, build methods, and establish how reliably those methods work.

You will own classifiers throughout their lifecycle—from supervised fine-tuning and distillation to deployment and production inference—while collaborating with researchers to identify valuable problems and with software engineers to scale approaches

Qualifications

• Experience taking ML projects from problem formulation and experimentation through production deployment.
• Strong foundations in supervised learning, statistics, and experimental design.
• Practical experience evaluating models, investigating systematic errors, and working with imperfect labels.
• Strong software engineering skills and the ability to build maintainable production ML systems.
• Experience reasoning about inference performance and the tradeoffs between quality, latency, and compute cost.
• The ability to combine careful scientific judgment with a practical approach to shipping and operating software.
• Comfort working closely with researchers and engineers on open-ended problems.
• Fluency in using AI agents to move quickly across multiple workstreams in a fast-paced environment.

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.
• Work with post-training researchers and data scientists to translate their needs into modeling objectives, evaluation criteria, and production requirements.

Skills

ML engineering

Supervised learning

Evaluation

Distillation

Inference optimization

Software engineering

Experiment design

Job description

OpenAI is seeking a machine learning engineer to develop and deploy classification and evaluation capabilities. You will turn open-ended questions about model behavior into ML problems, build methods, and establish how reliably those methods work.

You will own classifiers throughout their lifecycle—from supervised fine-tuning and distillation to deployment and production inference—while collaborating with researchers to identify valuable problems and with software engineers to scale approaches