Engineering Manager, RL Engineering

Anthropic's RL Engineering team builds the systems, allowing large-scale distributed reinforcement learning with language models. As manager of the team, you'll support a team of machine learning and distributed systems experts with the goal of making these systems highly efficient, supporting fast iteration on model development, and continuously evolving the infrastructure to incorporate new research advances.

Our reinforcement learning system sits at the intersection of almost every technical group at Anthropic. You'll work with research teams to incorporate their innovations into our production finetuning pipeline, product teams to help us iterate quickly on customer-oriented model improvements, and infrastructure teams to make sure our training runs are as efficient and reliable as possible.

Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. Our interdisciplinary team has experience across ML, engineering, physics, policy, business, and product.

• Prioritize the team's work in collaboration with the technical lead, research teams, and product teams to support fast iteration on research projects and training runs.
• Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively.
• Coach and support your reports to understand and pursue their professional growth.
• Run the team's recruiting efforts efficiently, ensuring we can grow as quickly as we need through a period of rapid growth.

• Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well
• Are an experienced manager (at least 1 year) and actively enjoy people management
• 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) to be effective

• Experience working with large language models or reinforcement learning
• Experience doing research in any domain or experience working with research teams, especially as part of a “research to production” pipeline
• Strong people management experience: Coaching, performance evaluation, mentorship, career development
• Strong project management skills: Prioritization, communicating across team/org boundaries
• Experience recruiting for your team: Predicting staffing needs, designing interview loops, evaluating candidates, and closing them

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.

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.

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.