Engineering Manager, Inference at Anthropic
- Company: Anthropic
- Location: San Francisco, CA | New York City, NY | Seattle, WA
- Employment type: full-time
- Posted: 2026-08-21
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role:
Anthropic’s performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast paced, dynamic environment.
Responsibilities:
- Provide front-line leadership of engineering efforts to improve model performance and scale our 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 your reports in understanding, and pursuing, their professional growth
- Maintain a deep understanding of the team's technical work and its implications for AI safety
You may be a good fit if you:
- Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
- Have a background in machine learning, AI, or a similar related technical field
- Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
- Excel at building strong relationships with stakeholders at all levels
- Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
- Have experience managing teams through periods of rapid growth and change
- Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level of abstraction) to be effective
Strong candidates may also have experience with:
- High performance, large-scale ML systems
- GPU/Accelerator programming
- ML framework internals
- OS internals
- Language modeling with transformers
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candi
Apply for this Engineering Manager, Inference role
More jobs at Anthropic
- AWS Partnerships Lead, DACH — Munich, Germany
- Policy Partnerships & Convenings Lead, Central Policy — San Francisco, CA; Washington, DC
- Head of Deal Desk - International — London, UK
- Marketing Events Lead, Enterprise — San Francisco, CA | New York City, NY
- Engineering Manager, Continuous Deployment and Change Safety — San Francisco, CA | New York City, NY
- Enterprise Intelligence Specialist — San Francisco, CA | New York City, NY | Washington, DC
- Evals Infrastructure Tech Lead / Manager — San Francisco, CA
- Data Scientist, Supply — San Francisco, CA | New York City, NY | Seattle, WA