Engineering Manager, ML Acceleration

Engineering Manager, ML Acceleration 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 What We're 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 (Optional) High performance, large-scale ML systems GPU/Accelerator programming ML framework internals OS internals Language modeling with transformers Compensation Annual Salary: $425,000—$560,000 USD. Logistics We require at least a Bachelor's degree in a related field or equivalent experience. 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 Meet Every 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. Come Work with Us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process. #J-18808-Ljbffr Anthropic