Anthropic Fellows Program — ML Systems & Performance

About the Role

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society as a whole. The company is committed to fostering a culture of innovation, collaboration, and continuous learning, and is looking for talented individuals who share this vision.

The program is designed to provide fellows with the support and resources they need to succeed, including direct mentorship from Anthropic researchers, access to a shared workspace, and connection to the broader AI safety and security research community.

What You Will Do

• Work on empirical projects aligned with Anthropic's research priorities, with a focus on ML systems and performance
• Develop and implement research plans, including designing and executing experiments, collecting and analyzing data, and drawing conclusions
• Collaborate with Anthropic researchers and other fellows to advance the field of AI research and engineering
• Produce a public output, such as a paper submission, as a result of your research
• Participate in regular meetings and discussions with your mentor and other fellows to share progress, receive feedback, and stay updated on relevant research and developments
• Stay up-to-date with the latest research and advancements in the field of AI, including reading relevant papers, attending conferences, and participating in online forums
• Contribute to the development of Anthropic's research priorities and goals
• Participate in the broader AI safety and security research community, including attending conferences, workshops, and other events
• Collaborate with other teams at Anthropic to advance the company's mission and goals

What We Are Looking For

• A strong foundation in machine learning, including experience with ML systems and performance
• Experience with empirical project development, including designing and executing experiments, collecting and analyzing data, and drawing conclusions
• Strong programming skills, including proficiency in languages such as Python, C++, or Java
• Experience with relevant tools and technologies, such as TensorFlow, PyTorch, or scikit-learn
• Excellent communication and collaboration skills, including the ability to work effectively with others, communicate complex ideas clearly, and receive feedback
• A passion for AI safety and beneficial AI systems, including a commitment to advancing the field and promoting responsible AI development
• A strong academic record, including a degree in a relevant field such as computer science, mathematics, or engineering
• Experience with research prioritization, including the ability to identify and pursue high-impact research projects

Nice to Have

• Experience with cloud computing, including platforms such as AWS or Google Cloud
• Familiarity with Agile development methodologies, including experience with iterative development and continuous delivery
• Experience with data visualization, including tools such as Tableau, Power BI, or D3.js
• Familiarity with DevOps practices, including experience with continuous integration and continuous deployment

Benefits and Perks

• Weekly stipend of $3,850 USD / 2,310 GBP / 4,300 CAD
• Funding for compute and other research expenses, including access to cutting-edge infrastructure and tools
• Direct mentorship from Anthropic researchers, including regular meetings and feedback
• Access to a shared workspace, including collaboration with other fellows and Anthropic researchers
• Connection to the broader AI safety and security research community, including attendance at conferences and workshops
• Opportunity to contribute to the development of Anthropic's research priorities and goals
• Collaborative and dynamic work environment, including a commitment to innovation, continuous learning, and teamwork

• Develop a strong foundation in machine learning, including experience with ML systems and performance, to increase your chances of success in this role.
• Showcase your ability to work independently and collaboratively, including experience with empirical project development and research prioritization.
• Highlight your passion for AI safety and beneficial AI systems, including a commitment to advancing the field and promoting responsible AI development.
• Be prepared to discuss your research experience and goals, including your ability to design and execute experiments, collect and analyze data, and draw conclusions.
• Emphasize your excellent communication and collaboration skills, including the ability to work effectively with others, communicate complex ideas clearly, and receive feedback.
• Consider showcasing your experience with relevant tools and technologies, such as TensorFlow, PyTorch, or scikit-learn, to demonstrate your technical expertise.