Engineering Manager, Inference

About the role

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.

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.

Requirements

• 1+ years of management experience in a technical environment, particularly performance or distributed systems.
• A background in machine learning, AI, or a similar related technical field.
• Deeply interested in the potential transformative effects of advanced AI systems and committed to ensuring their safe development.
• Excel at building strong relationships with stakeholders at all levels.
• A quick learner, capable of understanding and contributing to discussions on complex technical topics.
• Experience managing teams through periods of rapid growth and change.
• 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.

Qualifications

• 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.

Skills

• Effective communication skills.

Benefits

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.

Annual Salary $425,000—$560,000 USD

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

We currently 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 candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.

How We're Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us!

Guidance on Candidates' AI Usage

Learn about our policy for using AI in our application process.