About the position
The Center for AI Safety (CAIS) is a leading research and advocacy organization focused on mitigating societal-scale risks from AI. We address AI’s toughest challenges through technical research, field-building initiatives, and policy engagement, along with our partner 501(c)4 organization, Center for AI Safety Action Fund (CAISAF). We’re looking for a versatile Software Engineer to contribute to engineering projects and support our cloud-based GPU cluster. You will develop and maintain public-facing websites and internal tooling, enabling our research team to run experiments productively and demonstrate their results. In this role, you’ll also work with our cloud provider to maintain and scale our infrastructure and support cluster users with technical issues they face. Our cluster empowers a wide range of researchers (at Stanford, Berkeley, CMU, Cambridge, Harvard, and other top universities worldwide) who partner with CAIS to produce technical research on AI safety. Depending on the organization’s needs and your skillset, you may also contribute to engineering projects for other teams. This is a great opportunity for a mission-driven generalist engineer who enjoys operating at the intersection of software development and infrastructure and is excited to work on a wide variety of technical challenges.
Responsibilities
- Develop lightweight web-based tools, dashboards, and other services end-to-end.
- Maintain and update existing websites (e.g. static sites, research tools).
- Collaborate with research and operations teams to scope and implement new technical projects as needed.
- Maintain our cloud infrastructure and collaborate with service providers to ensure scalability, availability, and performance.
- Monitor cluster resource usage, generate reports, and support capacity planning to ensure efficient resource utilization.
Requirements
- Are a generalist full-stack engineer comfortable working on all parts of technical projects.
- Learn quickly and excel in fast-moving environments.
- Take proactive ownership of projects and enjoy collaborating with a small team.
- Have built web applications or custom tools (e.g. using Flask, Vercel, or static site generators).
- Have experience managing user-facing systems and responding to incidents in a timely manner.
- Care about making AI safer and advancing CAIS’ mission of mitigating societal-scale risks from AI.
Nice-to-haves
- Have experience provisioning and maintaining distributed systems using containerization tools such as Docker or Apptainer.
- Have a solid understanding of distributed systems including storage, networking, and security.
- Have worked with ML pipelines, HPC systems, or SLURM.
Benefits
- Health insurance for you and your dependents
- 401K plan + 4% matching
- Unlimited PTO
- Lunch and dinner at the office
- Annual Professional Development Stipend
- Access to some of the top talent working on technical and conceptual research in AI safety
