Engineering Manager, GPU (ML Accelerator)

Anthropic • $500K+*
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1+ years of management experience in a technical environment, especially performance or distributed systems
  • Background in machine learning, AI, or a related technical field
  • Commitment to the safe development of advanced AI systems
  • Ability to build strong stakeholder relationships
  • Experience managing teams during periods of rapid growth and change
  • Quick learner, capable of grasping complex technical topics

Responsibilities

  • Lead engineering efforts to enhance model performance and scale inference and training systems
  • Become familiar with the team's technical stack to contribute as an individual
  • Manage day-to-day execution of the team's projects
  • Prioritize team tasks in a dynamic, fast-paced environment
  • Coach and support team members in their professional development
  • Maintain understanding of technical work and its implications for AI safety

Benefits

  • Visa sponsorship available
  • Hybrid working policy with minimal office time requirements
  • Encouragement for diverse applicants to apply
  • Supportive coaching culture for professional growth
Full Job Description
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.

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.

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. 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links-visit anthropic.com/careers directly for confirmed position openings.

About Anthropic

Anthropic is an artificial intelligence research lab that focuses on developing AI systems that are safe, reliable, and trustworthy. The company was founded in 2019 by Dr. Yoshua Bengio, a leading AI researcher and winner of the Turing Award. Anthropic's research is focused on developing AI systems that can learn from small amounts of data, reason about complex systems, and interact with humans in a natural way. The company is based in New York City and has a team of experienced AI researchers and engineers.
Learn more about Anthropic
Size
50 employees
Industry
Founded
2019

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