TL;DR

Research Engineer / Research Scientist (AI): Developing the next generation of large language models with an accent on multimodal capabilities. Focus on model architecture, algorithms, data processing, and optimizing and scaling training infrastructure.

Location: Hybrid (Zürich, Switzerland). Expected to be in the office at least 25% of the time. Visa sponsorship is considered.

Company

Anthropic is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems for the benefit of society.

What you will do

  • Conduct research and implement solutions in model architecture, algorithms, data processing, and optimizer development.
  • Independently lead small research projects while collaborating with team members on larger initiatives.
  • Design, run, and analyze scientific experiments to advance understanding of large language models.
  • Optimize and scale training infrastructure to improve efficiency and reliability.
  • Develop and improve dev tooling to enhance team productivity.
  • Contribute to the entire stack, from low-level optimizations to high-level model design.

Requirements

  • Bachelor's degree in Computer Science, Machine Learning, or a related field.
  • Strong software engineering skills with a proven track record of building complex systems.
  • Expertise in Python and deep learning frameworks.
  • Experience with high-performance, large-scale ML systems, particularly in language modeling.
  • Familiarity with ML Accelerators, Kubernetes, and large-scale data processing.
  • Strong problem-solving and excellent communication skills.

Nice to have

  • Significant software engineering experience.
  • Ability to balance research goals with practical engineering constraints.
  • Enjoy pair programming and collaborative work.
  • Eager to learn more about machine learning research.
  • Enthusiasm for AI safety and general progress.

Culture & Benefits

  • Work as a single cohesive team on large-scale AI research efforts, prioritizing impact on steerable, trustworthy AI.
  • Approach AI research as an empirical science, similar to physics and biology.
  • Collaborative environment with frequent research discussions.
  • Offer competitive compensation and benefits, with optional equity donation matching.
  • Provide generous vacation and parental leave.
  • Flexible working hours and a collaborative office space.