About the Role
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Large, general systems of today can have significant benefits, but can also be unpredictable, unreliable, and opaque: our goal is to make progress on these issues.
How you’ll help us achieve it
You’ll lead the “inference service” team, which allows for fast and flexible sampling for all internal research teams and external users. This team has four critical responsibilities that all must be executed well in order for Anthropic to succeed:
1. Usability: Inference is the foundation of all our customer-facing applications (like Claude), as well as all of our internal research teams. You’ll need to make sure that our inference API is flexible enough for both of these use-cases, and that researchers can use it to be doing a wide variety of new experiments.
2. Reliability: Our partners are building businesses on top of Claude, and so this service needs to be highly available as we earn their trust.
3. Latency: Improving the speed at which Claude returns responses and generates additional text allows our partners to unlock entirely new use-cases and let Claude take on a wider variety of tasks.
4. Throughput: The efficiency of this service directly translates into how much total capacity we can take on, and how many users can access Claude.
As the team lead, you will:
Prioritize the team’s work in building and improving our inference systems, in collaboration with senior engineers and other stakeholders
Design processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively
Coach and develop your reports to decide how they would like to advance in their careers and help them do so
Run the team’s recruiting efforts through a period of rapid growth
You might enjoy this role if you…
Believe that advanced AI systems could have a transformative effect on the world, and are interested in helping make sure that transformation goes well.
Have an interest in large scale systems, performance engineering, and hardware.
Are an experienced manager and enjoy practicing management as a discipline.
You have at least 1 years of prior engineering management or equivalent experience
You can come into our San Francisco office at least 25% of the time
People management: Coaching, performance evaluation, mentorship, career development
Process design: Running a smooth on call rotation, incident response, postmortems, load testing, capacity planning, etc.
Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems
Project management: Prioritization, communicating across team/org boundaries
Recruiting: Predicting staffing needs, designing interview loops, evaluating candidates, closing
Compensation and Benefits*
Anthropic’s compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates.
Salary - The expected salary range for this position is $270k - $445k.
Equity - Equity will be a major component of the total compensation for this position. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance.
Benefits - Benefits we offer include:
- Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
- Comprehensive health, dental, and vision insurance for you and all your dependents.
- 401(k) plan with 4% matching.
- 21 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
- Stipends for education, home office improvements, commuting, and wellness.
- Fertility benefits via Carrot.
- Daily lunches and snacks in our office.
- Relocation support for those moving to the Bay Area.
* This compensation and benefits information is based on Anthropic’s good faith estimate for this position, in San Francisco, CA, as of the date of publication and may be modified in the future. The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.