Machine Learning, Research Engineer (Horizons)Dormont Manufacturing Company • San Francisco, California, United States
Machine Learning, Research Engineer (Horizons)
Dormont Manufacturing Company
- San Francisco, California, United States
- San Francisco, California, United States
Über
About Horizons The Horizons team leads Anthropic’s reinforcement learning research and development, playing a critical role in advancing our AI systems. We’ve contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude 3.5 and 3.7 Sonnet. Our work spans several key areas:
Developing systems that enable models to use computers effectively
Advancing code generation through reinforcement learning
Pioneering fundamental RL research for large language models
Building scalable RL infrastructure and training methodologies
Enhancing model reasoning capabilities
We collaborate closely with Anthropic’s alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and work hand‑in‑hand with dedicated RL engineering teams to implement our research at scale. The Horizons team sits at the intersection of cutting‑edge research and engineering excellence, with a deep commitment to building high‑quality, scalable systems that push the boundaries of what AI can accomplish.
About the Role As a Research Engineer on the Horizons team, 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. You’ll work on fundamental research in reinforcement learning, creating ‘agentic’ models via tool use for open‑ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation.
Representative projects
Architect 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.
You may be a good fit if you
Are proficient in Python and async/concurrent programming with frameworks like Trio
Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX)
Have industry experience in machine learning research
Can balance research exploration with engineering implementation
Enjoy pair programming (we love to pair!)
Care about code quality, testing, and performance
Have strong systems design and communication skills
Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems
Strong candidates may have
Familiarity with LLM architectures and training methodologies
Experience with reinforcement learning techniques and environments
Experience with virtualization and sandboxed code execution environments
Experience with Kubernetes
Experience with distributed systems or high‑performance computing
Experience with Rust and/or C++
Strong candidates need not have
Formal certifications or education credentials Academic research experience or publication history
Deadline to apply None. Applications will be reviewed on a rolling basis.
Salary The expected salary range for this position is: $340,000—$690,000 USD.
Logistics Education requirements We require at least a Bachelor’s degree in a related field or equivalent experience.
Location-based hybrid policy 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.
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.
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Sprachkenntnisse
- English
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