Engineering Manager, ML Performance and Scaling

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The performance and scaling teams focus on making the most efficient and impactful use of compute resources for both inference and training. As an Engineering Manager on these teams you will ensure your team identifies and removes bottlenecks, builds robust and durable solutions, and maximizes system efficiency. You will 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 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

Requirements

• 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Background in machine learning, AI, or a similar 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 learn and contribute to discussions on complex technical topics
• Experience managing teams through periods of rapid growth and change
• Comfortable understanding many complex technical systems at a high level of abstraction

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

Logistics

• Education: At least a Bachelor's degree in a related field or equivalent experience
• Location-based hybrid policy: staff expected to be in one of Anthropic's offices at least 25% of the time (some roles may require more)
• Visa sponsorship: Anthropic does sponsor visas and retains immigration counsel; sponsorship ability varies by role and candidate

Benefits

• Competitive compensation
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours and office space for collaboration

How we're different

Anthropic works as a single cohesive team on a few large-scale research efforts, valuing high-impact AI research, collaboration, and strong communication. Their research directions build on prior work such as GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Guidance on Applications

Anthropic encourages applicants even if they don't meet every listed qualification and values diverse perspectives. They provide guidance on candidate AI usage in the application process.