Engineering Manager (GPU, ML Accelerator)

• 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
• Provide front-line leadership of engineering efforts to improve model performance and scalr 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

Benefits

• Comprehensive health, dental, and vision insurance for you and your dependents

• Inclusive fertility benefits via Carrot Fertility

• 22 weeks of paid parental leave

• Flexible paid time off and absence policies

• Mental health support for you and your dependents

• Competitive salary and equity packages

• Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant

• Retirement plans with competitive matching

• Life and income protection plans

• $500/month flexible wellness and time saver stipend

• Commuter benefits

• Annual education stipend

• Home office stipends

• Relocation support for those moving for Anthropic

• Daily meals and snacks in the office

• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics

• 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

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems

• Excel at building strong relationships with stakeholders at all levels

• Have experience managing teams through periods of rapid growth and change

• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development

• Have a background in machine learning, AI, or a similar related technical field

• Language modeling with transformers

• ML framework internals

• OS internals

• GPU/Accelerator programming

• High performance, large-scale ML systems