Engineering Manager, AI Performance & GPU Scaling

Anthropic Limited; New York (NY); Hybrid; USD 500,000 - 850,000; Full time

Benefits offered by this job

Optional equity donation matching

Generous vacation and parental leave

Flexible working hours

Lovely office space to collaborate

Job summary

Anthropic is seeking an Engineering Manager for performance and scaling teams in New York. You will lead front-line engineering efforts to improve model performance and scale inference and training systems, while contributing as an IC when needed.

You will manage day-to-day execution, prioritize work, coach your reports, and maintain a strong focus on AI safety implications. A background in ML/AI and 1+ years of management in a technical environment are required.

Qualifications

• 1+ years of management experience in a technical environment (performance or distributed systems).
• Background in machine learning, AI, or related technical field.
• Interested in the transformative potential of advanced AI and safe development.
• Excellent relationship-building with stakeholders at all levels.
• Able to learn quickly and contribute to complex technical discussions.
• Experience leading teams through rapid growth and change.

Responsibilities

• Provide front-line engineering leadership to improve model performance and scale inference and training systems.
• Contribute as an individual contributor after becoming familiar with the stack.
• Manage day-to-day execution of the team's work.
• Prioritize the team's work and manage projects in a fast-paced environment.
• Coach reports and support professional growth.
• Maintain awareness of AI safety implications of the team's work.

Skills

Management experience

ML/AI background

Stakeholder management

Rapid growth experience

Technical leadership

Education

Bachelor's degree

Job description

Anthropic is seeking an Engineering Manager for performance and scaling teams in New York. You will lead front-line engineering efforts to improve model performance and scale inference and training systems, while contributing as an IC when needed.

You will manage day-to-day execution, prioritize work, coach your reports, and maintain a strong focus on AI safety implications. A background in ML/AI and 1+ years of management in a technical environment are required.