Engineering Manager, RL Engineering

As the Engineering Manager for RL Engineering at Anthropic, you will oversee a team of experts in machine learning and distributed systems. Your primary responsibilities include prioritizing teamwork, designing effective operational processes, coaching your team members for professional growth, and streamlining recruiting efforts to build a strong, capable team. You'll also collaborate with various technical groups within Anthropic to advance our reinforcement learning capabilities.

For the Engineering Manager position at Anthropic, candidates should have at least one year of management experience and a strong interest in people management. Knowledge in large language models or reinforcement learning and familiarity with the research-to-production pipeline will be advantageous. Furthermore, strong project management, coaching, and recruiting skills are essential for effectively leading the team.

The Engineering Manager at Anthropic plays a crucial role in ensuring that our reinforcement learning systems are built and maintained with a focus on safety and efficiency. By facilitating collaboration across research, product, and infrastructure teams, you'll help integrate innovative solutions that prioritize responsible AI development, which aligns with our mission to create reliable, interpretable, and steerable AI systems.

As an Engineering Manager at Anthropic, you'll have numerous collaborative opportunities across various teams. The RL Engineering team interacts closely with research teams to incorporate cutting-edge innovations, product teams for rapid customer-oriented improvements, and infrastructure teams to enhance the efficiency of training runs—making this a truly integrative role in a dynamic environment.

Anthropic champions a collaborative and inclusive company culture. As an Engineering Manager, you'll be part of a diverse team that values open communication and shared goals. The culture places significant importance on professional development and diverse perspectives, ensuring every team member feels empowered and equipped to contribute to our mission of advancing beneficial AI systems.

In answering this question, highlight specific experiences managing technical teams, focusing on your leadership style, how you foster collaboration, and your approach to project management. Provide examples of challenges you faced and how you helped your team overcome them.

Discuss your methods for prioritizing tasks, such as using frameworks like the Eisenhower Matrix or Agile methodologies. Talk about your experience with stakeholder communication and setting clear expectations to keep everyone aligned during busy periods.

Share concrete strategies you utilize for mentoring, including regular one-on-one check-ins, setting clear developmental goals, and providing constructive feedback. Emphasize the importance of fostering a growth mindset within your team to enhance skills and morale.

Explain your approach to conflict resolution by mentioning how you promote open communication, encourage team members to express their viewpoints, and facilitate discussions to reach common ground. Provide an example of a conflict you successfully mediated.

Highlight any direct experience you have with large language models or reinforcement learning, whether through previous roles or projects. Demonstrating an understanding of these technologies will show your relevance for the Engineering Manager position.

Mention specific practices you implement to keep your team informed about the latest AI research—this can include dedicated research meetings, sharing relevant publications, or encouraging attendance at industry conferences. Illustrate how this knowledge translates into team performance.

Use this question to discuss a project you led from inception to production, detailing your role, the methodologies you applied, and the outcomes. Focus on how you coordinated efforts across teams and any innovative solutions you implemented.

Explain how you set metrics for success, both qualitatively and quantitatively. Discuss how you assess team dynamics and project outcomes to ensure alignment with company objectives and goals, thereby demonstrating accountability.

Share your views on the ethical implications of AI and the importance of safety in AI systems. Articulate how these considerations influence your work and leadership style and how you intend to integrate ethical practices in your team's projects.

Discuss your recruiting philosophy, including how you design interview processes to evaluate not just technical skills but cultural fit and growth potential. Illustrate how you predict staffing needs and attract diverse candidates to join your team.