ML Agent Engineer

Summary

We're seeking research engineers to build systems for breakthrough innovations in AI agents, reinforcement learning, and simulation environments. You will design and implement high-quality agent harnesses, simulation systems, and tooling that enable cutting-edge agent research. You will work in an organization of world-class machine learning researchers and engineers. Our work powers technologies across the Apple ecosystem and is published in the most selective scientific journals and conferences.

Minimum Qualifications

Bachelors in Computer Science/Electrical Engineering or equivalent academic or professional experience. 2+ years of ML engineering experience building and maintaining training and inference systems - including model harnesses, training infrastructure, model serving, or evaluation frameworks. Solid software engineering skills in complex systems - Fluency in Python. You deliver clean, well-tested code. Hands-on experience with distributed ML systems - CI/CD at scale, distributed testing, or ML evaluation pipelines. Proficiency with ML modeling frameworks (PyTorch, Tensorflow, etc.). Proven track record shipping ML systems end-to-end - from problem framing and data curation through training, evaluation, deployment, and monitoring in production.

Preferred Qualifications

MS or PhD in Computer Science, Engineering, Math, or Physics from a strong program. Familiarity with macOS/iOS development ecosystems. Active personal interest in AI agents—you're already experimenting on your own time.

Description

We are a team of best-in-the-world research scientists and engineers focused on building best-in-class AI agents. Our work spans the entire AI agent system stack, including model training, harness design, evaluation, and deployment. We work on exciting new technologies that bring joy to millions of people. In our daily work, the team stays innovative, productive, and fun by sharing some key values:

Responsibilities

Passion for the mission: We're here to make something extraordinary. We seek whatever work is right and strive for the best possible results. Modesty: The right answer is more significant than being right. We search for solutions as a team and value clear-eyed feedback. Lean habits: You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.