Machine Learning Engineer, API Multicloud

Job summary

Responsibilities

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.

• 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…
• Build and scale production ML systems for model customization, post-training, and fine-tuning-as-a-service workflows.
• Design, run, and interpret experiments to see whether training and customization workflows are producing the intended outcomes, and identify changes to data, evaluation…
• 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.

What they're looking for

• Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
• 3+ 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…
• Hands-on experience with training and fine-tuning large language models, including methods like supervised fine-tuning, distillation, preference optimization, reinforcement…
• Strong software engineering fundamentals, including data structures, algorithms, systems design, and high-quality production code in Python, Rust, or similar languages.

Tech stack

• AWS
• PyTorch
• TensorFlow
• Python
• Rust