Research Engineer, Machine Learning (Reinforcement Learning)
About the role
As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction.
Responsibilities
- Arcitect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters.
- Help scale our systems to handle increasingly complex research workflows.
- Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models.
- Drive performance improvements across our stack through profiling, optimization, and benchmarking.
- Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows.
- Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research.
Requirements
- Proficient in Python and async/concurrent programming with frameworks like Trio
- Experience with machine learning frameworks (PyTorch, TensorFlow, JAX)
- Industry experience in machine learning research
- Balanced research exploration with engineering implementation
- Enjoy pair programming (we love to pair!)
- Strong systems design and communication skills
- Pasisonate about the potential impact of AI and committed to developing safe and beneficial systems
Qualifications
- Strong Candidate May Have Familiarity with LLM architectures and training methodologies
- Experience with reinforcement learning techniques and environments
- Familiarity with virtualization and sandboxed code execution environments
- Experience with Kubernetes
- Experience with distributed systems or high-performance computing
- Experience with Rust and/or C++
Skills
- Python and async/concurrent programming
- Machine learning frameworks (PyTorch, TensorFlow, JAX)
- Research and engineering experience
- Communication and collaboration skills
- Systems design and performance optimization
- Reinforcement learning techniques and environments
- Virtualization and sandboxed code execution environments
- Kubernetes
- Distributed systems or high-performance computing
- Rust and/or C++
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Lovely office space for collaboration
Pay
The annual compensation range for this role is $500,000—$850,000 USD.
Schedule
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Location-based Hybrid Policy
We currently expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa Sponsorship
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
Guidance on Candidates' AI Usage
We believe that the easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.