Used Tools & Technologies
Not specified
Required Skills & Competences ?
Kubernetes @ 3 Python @ 3 Algorithms @ 3 Distributed Systems @ 3 Machine Learning @ 3 LLM @ 3Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems to ensure AI is safe and beneficial for users and society. The team is composed of researchers, engineers, policy experts, and business leaders committed to building beneficial AI systems.
Responsibilities
- Build cutting-edge systems that train AI models like Claude.
- Implement and improve advanced techniques to create more capable, reliable, and steerable AI.
- Develop and maintain critical algorithms and infrastructure to support researchers training models.
- Improve performance, robustness, and usability of training systems.
- Support and empower the research team to advance AI capabilities and safety.
- Maintain and enhance algorithms and systems used for training models, including improving speed, reliability, and ease-of-use.
Requirements
- Minimum 2+ years of software engineering experience.
- Passion for building systems and tools that increase productivity.
- Results-oriented mindset with flexibility and impact focus.
- Willingness to take on diverse tasks beyond job description.
- Enjoy pair programming.
- Interest in learning about machine learning research.
- Concern for societal impacts of work.
Strong candidates may also have experience with:
- High performance, large scale distributed systems
- Kubernetes
- Python
- Implementing LLM finetuning algorithms such as RLHF
Representative Projects
- Profiling reinforcement learning pipelines to find improvements
- Building systems to launch training jobs for quick problem detection
- Updating finetuning systems for new model architectures
- Creating instrumentation to eliminate Python GIL contention
- Diagnosing and fixing training slowdowns
- Implementing stable, fast versions of new training algorithms
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Hybrid office policy with at least 25% office presence
- Visa sponsorship support
- Collaborative, impact-focused AI research environment