Research Engineer, Infrastructure

We are an applied AI lab building end-to-end software agents. We're the team behind Devin, the first AI software engineer, and Windsurf, an AI-native IDE. This role exists to make sure nothing in the stack becomes the bottleneck that slows down the frontier. You will own the core systems that researchers depend on daily: distributed training infrastructure, experiment orchestration, data pipelines, and the tooling that turns raw compute into usable research velocity.

Requirements

• Deep experience building and operating distributed training systems for large models
• Strong systems engineering fundamentals: distributed systems, networking, storage, and the ability to reason about performance across the full hardware-software stack
• Proficiency in Python and C++; experience with PyTorch or equivalent deep learning frameworks at a systems level, not just API usage
• Hands-on experience with GPU performance profiling, memory optimization, and compute efficiency
• Experience implementing or optimizing parallelism strategies (data, tensor, pipeline, sequence) for large model training
• Track record of building tooling and abstractions that meaningfully accelerate research workflows
• Strong debugging instincts across complex, distributed systems where failures are non-deterministic and hard to reproduce
• Enough ML knowledge to engage substantively with researchers: understand what they are training, why the architecture choices matter, and what the infrastructure needs to support

Benefits

• Medical, dental, and vision insurance
• 401(k) matching
• Flexible PTO
• Professional development opportunities
• Catered meals and snacks
• Relocation assistance