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Research Scientist
2 months ago
At Anthropic, our mission is to create AI systems that are reliable, interpretable, and steerable. We aim to make AI safe and beneficial for users and society as a whole. Our team is a collaborative group of researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
Job SummaryWe are seeking a highly skilled Research Engineer to join our team. As a Research Engineer, you will play a key role in designing and developing large-scale machine learning systems from the ground up. You will work closely with our team to create safe, steerable, and trustworthy AI systems.
Key Responsibilities- Design and develop large-scale machine learning systems
- Collaborate with the team to create safe, steerable, and trustworthy AI systems
- Work on improving the reliability and efficiency of our code and infrastructure
- Run and design scientific experiments to improve our AI systems
- Improve our dev tooling and infrastructure
- Significant software engineering experience
- Results-oriented with a bias towards flexibility and impact
- Pick up slack and take on additional responsibilities
- Enjoy pair programming and collaboration
- Want to learn more about machine learning research
- Care about the societal impacts of AI
- Experience with high-performance, large-scale ML systems
- Knowledge of GPUs, Kubernetes, PyTorch, or OS internals
- Experience with language modeling with transformers
- Experience with reinforcement learning
- Experience with large-scale ETL
- Competitive salary range: £225,000—£340,000 GBP
- Equity compensation
- Comprehensive health, dental, and vision insurance
- 22 weeks of paid parental leave
- Unlimited PTO
- Stipends for education, home office improvements, commuting, and wellness
- Daily lunches and snacks in our office
- Relocation support for those moving to the Bay Area
We believe that the highest-impact AI research will be big science. At Anthropic, we work as a single cohesive team on just a few large-scale research efforts. We value impact and advancing our long-term goals of steerable, trustworthy AI. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time.