Research Software Engineer, Post Training
Build and operate the engineering systems that support post-training research, including reinforcement learning infrastructure, sandboxed execution, data pipelines, and agent scaffolding. The role requires strong Python and systems engineering skills, project ownership, and a relevant bachelor’s degree or equivalent experience.
About the job
Responsibilities
- Embed within a research team to build, harden, and improve the systems and infrastructure required for its work.
- Design, build, and operate infrastructure including reinforcement learning training systems, sandboxing, data pipelines, and agent scaffolding.
- Lead projects end to end and contribute to large, fast-moving codebases.
- Debug systems that fail intermittently and at scale.
- Explain complex technical concepts clearly in writing.
Requirements
- Strong proficiency in Python and strong engineering fundamentals.
- Experience leading projects end to end and writing code that others depend on.
- Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline.
- Strong theoretical and empirical grounding.
- Autonomous, ownership-oriented approach to advancing team goals.
Nice-to-haves
- Experience building or iterating on sandboxed or containerized execution environments at large scale.
- Experience working in roles where team priorities determine individual priorities.
- Familiarity with at least one deep learning framework, such as PyTorch, TensorFlow, or JAX.
Compensation and Benefits
- Expected annual salary: $350,000-$475,000 USD, depending on background, skills, and experience.
- Health, dental, and vision benefits.
- Unlimited paid time off.
- Paid parental leave.
- Relocation support.
- Visa sponsorship.
Skills
Python, Reinforcement Learning, Containerization, Data Pipelines, Deep Learning, PyTorch, TensorFlow, JAX, Sandboxing, Machine Learning
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