Engineering Manager, GPU (ML Accelerator)

Polluxa, Inc.; San Francisco (CA); Hybrid; USD 500,000 - 850,000; Full time

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation

Parental leave

Flexible working hours

Office space

Job summary

Anthropic is seeking an Engineering Manager to lead performance and scaling efforts for inference and training systems. You will guide bottleneck removal, build robust solutions, and maximize efficiency while aligning teams in a fast-paced setting.

You will mentor engineers, manage projects through rapid growth, and ensure AI safety considerations are integrated into technical decisions. This role sits in a highly collaborative environment in San Francisco.

Qualifications

• 1+ years of management experience in a technical environment.
• Background in machine learning, AI, or a similar technical field.
• Interest in transformative AI and safe development.
• Excel at building relationships with stakeholders at all levels.
• Quick learner capable of understanding complex technical topics.
• Experience leading teams through periods of rapid growth and change.

Responsibilities

• Provide front-line leadership to improve model performance and scale inference and training systems.
• Familiarize with the team's stack to contribute as an individual contributor.
• Manage day-to-day execution of the team’s work.
• Prioritize the team’s work and manage projects in a dynamic environment.
• Coach and support reports in their professional growth.
• Maintain understanding of the team’s work and its AI safety implications.

Skills

Management experience

Machine learning background

Stakeholder relationships

Fast learner

Team leadership

Problem solving

Education

Bachelor's degree in a field relevant to the role

Tools

GPU/Accelerator programming

Job description

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

Who we are looking for

• 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

Additional experience

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

Annual compensation

Annual Salary: $500,000 - $850,000 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: 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 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.

Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

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.

Benefits and Perks

• competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. Guidance on Candidates' AI Usage: Learn about [our policy](https://www.anthropic.com/candidate-ai-guidance) for using AI in our application process.