Machine Learning Engineer, API Multicloud

Highlights

• Extend OpenAI's API platform into AWS-native environments for strategic partners.
• Build production systems for fine-tuning-as-a-service and agentic workloads.
• Turn partner deployments into scalable improvements to post-training platform.

What they offer

• Equity

Ideal candidate

ML engineer who thrives in 0→1 ambiguity and enjoys partnering with external teams to diagnose model behavior and turn messy needs into reliable production systems.

Requirements

• Master's or PhD in Computer Science, Machine Learning, or related field, or equivalent practical experience.
• 3+ years of professional engineering experience in relevant ML, infrastructure, or product-driven roles.
• Strong ML engineering experience building, training, fine-tuning, evaluating, or deploying production AI systems.
• Hands-on experience with LLM post-training methods like SFT, distillation, preference optimization, or RL.
• Strong software engineering fundamentals and high-quality production code in Python, Rust, or similar.
• Experience with evaluation systems, data pipelines, distributed systems, cloud infrastructure, or ML platforms.
• Ability to operate across model behavior, APIs, and infrastructure with Research, Safety, and external partners.
• Comfort owning problems end-to-end through ambiguity and learning what is needed to deliver.