Research Scientist

4 weeks ago


London, Greater London, United Kingdom DALLAS VA RESEARCH CORPORATION Full time
About Anthropic

At Anthropic, we're dedicated to creating AI systems that are reliable, interpretable, and steerable. Our mission is to develop AI that benefits society as a whole, and we're committed to making a positive impact. As a Research Engineer, you'll play a key role in shaping our code and infrastructure, ensuring that our AI systems are safe, trustworthy, and beneficial.

Key Responsibilities
  • Design and develop large-scale ML systems from the ground up
  • Collaborate with our team to improve our code and infrastructure
  • Run and design scientific experiments to advance our research
  • Improve our dev tooling to ensure seamless collaboration
Requirements
  • Significant software engineering experience
  • Results-oriented with a bias towards flexibility and impact
  • Ability to pick up slack and adapt to changing priorities
  • Experience with pair programming and a willingness to learn
  • Passion for machine learning research and its societal implications
Preferred Qualifications
  • Experience with high-performance, large-scale ML systems
  • Knowledge of GPUs, Kubernetes, PyTorch, or OS internals
  • Background in language modeling with transformers
  • Experience with reinforcement learning
  • Skills in large-scale ETL
What We Offer
  • Competitive salary range: £225,000—£340,000 GBP
  • Equity in the company
  • 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
How We're Different

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, with 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're pursuing the highest-impact work at any given time.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.


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