Machine Learning Engineer, API Multicloud · OpenAI

Fri, 24 Apr 2026 12:20:36 GMT
Engineering

OpenAI · San Francisco · $295K – $445K · onsite

Compensation

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following 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 (1 hour per 30 hours worked, or more, as required by applicable state or local law)

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

Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

OpenAI's API Multicloud team sits within B2B Applications and is responsible for extending OpenAI's API platform into strategic cloud environments, starting with AWS. The team's mission is to distribute OpenAI's API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied.

About the Role

We're hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration.

You'll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn't working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You'll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time.

In this role, you will

Partner with strategic customers and internal teams to define target model behaviors, diagnose failure modes, and translate real-world needs into training, evaluation, and system requirements.

Build and scale production ML systems for model customization, post-training, and fine-tuning-as-a-service workflows.

Investigate whether training and customization workflows are producing the intended outcomes, and identify changes to data, evaluation, training, or infrastructure that improve performance.

Partner with backend and infrastructure engineers to integrate ML capabilities into AWS-native API environments.

Feed learnings from partner deployments back into the platform by proposing and implementing improvements to post-training systems, tooling, APIs, and developer workflows.

Work closely with Research and Applied teams to bring model improvements, training workflows, and evaluation best practices into production.

Help design systems that allow strategic partners and enterprise customers to safely customize OpenAI models for high-value use cases.

Debug and improve complex systems spanning model behavior, training data, APIs, distributed infrastructure, and customer-facing product surfaces.

Operate with high ownership in a 0→1 environment where requirements are ambiguous, systems are evolving quickly, and reliability matters.

Your background might look something like:

Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.

7+ years of professional engineering experience in relevant ML, infrastructure, or product-driven engineering roles.

Strong ML engineering experience building, training, fine-tuning, evaluating, or deploying production AI systems, with hands-on experience in deep learning, transformer models, and frameworks like PyTorch or TensorFlow.

Familiarity with training and fine-tuning large language models, including methods like supervised fine-tuning, distillation, preference optimization, reinforcement learning, or other post-training techniques.

Strong software engineering fundamentals, including data structures, algorithms, systems design, and high-quality production code in Python, Rust, or similar languages.

Experience with model customization, evaluation systems, data pipelines, distributed systems, cloud infrastructure, or production ML platform tradeoffs.

Ability to operate across model behavior, APIs, and infrastructure, while collaborating closely with Research, Safety, product engineering, infrastructure, and external technical partners.

Comfort moving quickly through ambiguity, owning problems end-to-end, and learning whatever is needed to get the job done.

Bonus: experience with AWS, Kubernetes, agents, tool use, runtime environments, AI developer platforms, or speech models.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see [OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement](https://cdn.openai.com/policies/eeo-policy-statement.pdf).

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Initiative, and the New York City Fair Chance Act.