Engineering Manager, Inference
San Francisco, CA | New York City, NY | Seattle, WAFull-TimeManagerSoftware Engineering
About Anthropic
- 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
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.
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.
