Software Engineer, ML Systems & Training Architecture
Hands-on senior software engineer focused on maintaining and improving ML training infrastructure, debugging training systems, and unblocking researchers on the robotics team.
About the job
Responsibilities
- Review, improve, and clean up code across training frameworks and adjacent infrastructure
- Identify risky or low-quality changes before they land, and raise the code quality bar without slowing the team down
- Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure
- Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling
- Improve the reliability, maintainability, and usability of the robotics team's training framework
- Move quickly on practical engineering problems that directly affect team velocity
Requirements
- Strong software engineering fundamentals and excellent code review judgment
- Experience with ML systems, training frameworks, GPUs, distributed systems, infrastructure, or similarly complex technical environments
- Ability to read and debug unfamiliar codebases quickly, and enjoy getting to root cause
- Ship high-quality code with strong velocity and pragmatic judgment
- Low-ego, responsive, and motivated by helping researchers and engineers move faster
- Prefer being a highly effective hands-on IC over driving broad process-heavy initiatives
- Experience reviewing messy, fast-moving, or AI-generated codebases
Skills
Python, PyTorch, TensorFlow, CUDA, Distributed Systems, Gpu Programming, Ml Training Frameworks, Code Review, Debugging, Infrastructure
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