# Research Engineer, Code RL

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY
**Role:** ML Engineering
**Salary:** $500k – $850k/yr
**Experience:** 7+ years
**Skills:** Python, Reinforcement Learning, PyTorch, CUDA, Gpu Programming, Distributed Training, Async Programming, Code Execution Sandboxes, Program Analysis, Formal Methods
**Posted:** 2026-06-11

> Research Engineer advancing Claude's code generation capabilities through reinforcement learning. Design RL environments, build verifiers, run training experiments on frontier models, and improve training pipelines for real software engineering tasks.

## Job Description

## Responsibilities
- Design RL environments and coding tasks for training models on real software engineering work
- Build reward signals and verifiers that capture what "good code" means
- Run training experiments on frontier models
- Diagnose why models do or don't improve at classes of software-engineering work
- Improve speed and reliability of training pipelines
- Advance models' ability to write, edit, test, debug, and ship real software end-to-end

## Requirements
- Strong software-engineering skills and deep Python expertise, including async/concurrent programming
- Comfortable owning systems end to end and debugging across the stack
- Ability to balance research exploration with engineering implementation
- Rigorous approach to experimental design and interpreting results
- Care about code quality, testing, and performance
- Commitment to developing safe and beneficial AI systems
- Bachelor's degree or equivalent combination of education, training, and/or experience in a relevant field

## Nice-to-Haves
- Experience with reinforcement learning, RLHF, post-training, or LLM finetuning
- Experience building coding agents, code-execution sandboxes, eval harnesses, verifiers, or developer tooling
- Background in program analysis, testing, verification, compilers, or formal methods
- Experience with PyTorch and large-scale distributed training; performance profiling and optimization of ML systems
- CUDA / GPU or TPU kernel experience and accelerator-performance intuition
- Experience with virtualization and sandboxed code execution environments

## Compensation & Benefits
- Annual Salary: $500,000—$850,000 USD
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Visa sponsorship available

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