Research Engineer, Infrastructure

📋 Description

• Scale the post-training stack, supporting SFT and RL on leading open-weight models.
• Build distributed rollout infrastructure that coordinates model inference, tool execution, and
• Build infrastructure for reproducible agent environments where models can interact with documents
• Own performance and reliability of training runs, including GPU utilization, checkpointing, failure
• Identify and remove bottlenecks across training and inference to shorten the path from research
• Build internal tools and services for training data management, running evals, and

🎯 Requirements

• Experience building ML infrastructure, distributed systems, or research tooling.
• Strong Python and generalist software engineering skills across backend services, data systems, and
• Familiarity with PyTorch, JAX, or similar ML frameworks.
• Experience with distributed training or inference, including diagnosing performance bottlenecks and
• Understanding of post-training workflows; experience with RL rollouts, agent environments, or
• Practical judgment about what to build versus adopt, and the ability to partner with researchers

🎁 Benefits

• $230K – $340K base salary range
• Equity
• Bonus
• Applicant privacy notice applicable depending on location