Engineering Manager, GPU (ML Accelerator)

at Anthropic

📍 New York City, United States
📍 San Francisco, United States
📍 Seattle, United States

USD 500,000-850,000 per year

MIDDLE

✅ Hybrid

✅ Visa Sponsorship

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 Distributed Systems @ 3 GPU Machine Learning @ 3

Details

Anthropic's performance and scaling teams focus on making the most efficient and impactful use of compute resources for inference and training. The Engineering Manager will lead a team responsible for identifying and removing bottlenecks, building robust and durable solutions, maximizing system efficiency, and providing clarity, focus, and context in a fast-paced environment.

Responsibilities

Provide front-line leadership of engineering efforts to improve model performance and scale inference and training systems.
Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor.
Manage day-to-day execution of the team's work.
Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment.
Coach and support reports in understanding and pursuing their professional growth.
Maintain a deep understanding of the team's technical work and its implications for AI safety.

Requirements

At least 1 year of management experience in a technical environment, particularly performance or distributed systems.
Background in machine learning, artificial intelligence, or a related technical field.
Deep interest in the potential transformative effects of advanced AI systems and commitment to their safe development.
Strong relationship-building skills with stakeholders at all levels.
Ability to quickly understand and contribute to discussions on complex technical topics.
Experience managing teams through periods of rapid growth and change.
Ability to understand a broad range of complex technical systems at a high level of abstraction.

Preferred Experience

High-performance, large-scale machine learning systems.
GPU or accelerator programming.
Machine learning framework internals.
Operating system internals.
Language modeling with transformers.

Education And Experience

Bachelor's degree or an equivalent combination of education, training, and experience.
Field of study relevant to the role, demonstrated through coursework, training, or professional experience.
Required years of experience correlate with the internal job-level requirements for the position.

Benefits

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space for collaboration.