Software Engineer, Anthropic

• 5+ years of industry-related experience
• Are proficient in Python and async/concurrent programming with frameworks like Trio
• Have a strong software engineering background and are interested in working closely with researchers and other engineers
• 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
• Candidates need not have:
• Formal certifications or education credentials
• Experience with LLMs, reinforcement learning, or machine learning research before

Desirable

• As a Software 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 through fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use, improving reasoning abilities in areas such as code generation and mathematics, and developing prototypes for internal use, productivity, and evaluation
• Design and maintain high-performance data pipelines for processing large-scale code datasets and implementing secure sandboxed execution environments
• 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
• Build intuitive developer tools and dashboards for analyzing ML experiments, including real-time visualizations, interactive debugging interfaces, and efficient metrics collection systems that help researchers understand model behavior
• 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