ML Engineer: Multicloud API & Post-Training (AWS)

OpenAI; San Francisco (CA); On-site; USD 295,000 - 445,000; Full time

Job summary

OpenAI is seeking a Machine Learning Engineer to build and scale AI systems that help strategic partners adapt OpenAI models to cloud-native environments, starting with AWS. This role covers post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration.

You will collaborate with Research, Applied, Safety Systems, and external partners to diagnose issues, run experiments, and implement improvements that raise model quality and reliability while delivering

Qualifications

• Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
• 3+ years of professional engineering experience in ML, infrastructure, or product-driven roles.
• Hands-on experience with training and fine-tuning large language models.

Responsibilities

• Define target model behaviors with strategic customers and translate needs into training, evaluation, and system requirements.
• Build and scale production ML systems for model customization and post-training workflows.
• Design, run, and interpret experiments to improve data, evaluation, training, or infrastructure.
• Integrate ML capabilities into cloud-native API environments with backend teams.
• Propose and implement improvements to post-training systems, tooling, and developer workflows.
• Collaborate with Research, Applied, Safety Systems, and external partners to productionize model improvements.

Skills

ML engineering fundamentals

Python

PyTorch

TensorFlow

Data pipelines

Systems design

CLOUD infrastructure

Education

Master’s/PhD in CS or related field

Tools

PyTorch

TensorFlow

Python

Rust

Job description

OpenAI is seeking a Machine Learning Engineer to build and scale AI systems that help strategic partners adapt OpenAI models to cloud-native environments, starting with AWS. This role covers post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration.

You will collaborate with Research, Applied, Safety Systems, and external partners to diagnose issues, run experiments, and implement improvements that raise model quality and reliability while delivering