Technical Program Manager, Inference Performance
San Francisco, CA | Seattle, WAFull-TimeManagerProduct / Project
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
- As a Technical Program Manager for Inference, you'll be the critical bridge between our inference systems and the broader organization. You'll drive strategic initiatives across inference runtime and accelerator performance—coordinating model launches, managing cross-platform dependencies, and ensuring reliability across multiple hardware targets. This role is essential for keeping our most contended infrastructure teams shipping effectively while Research, Product, and Safety all depend on their output.
Responsibilities
- Systems Integration & Coordination: Lead cross-functional initiatives for new infrastructure integration, establishing clear ownership, timelines, and communication channels between teams. Drive end-to-end planning for major infrastructure transitions including platform modernization and new tech adoption.
- Performance & Efficiency: Partner with engineering teams to identify optimization opportunities, track performance metrics, and prioritize work that unlocks capacity gains. Coordinate across runtime and accelerator layers to ensure efficiency wins ship without compromising reliability.
- Launch Coordination: Drive end-to-end readiness for model and feature launches across multiple hardware platforms. Establish processes for cross-platform validation, manage launch timelines, and ensure smooth handoffs between runtime, accelerator, and downstream teams.
- Strategic Planning: Own and prioritize the inference deployment roadmap, working closely with engineering leadership to prioritize initiatives and manage dependencies. Provide visibility into upcoming changes and their organizational impact.
- Stakeholder Communication: Build strong relationships across research, engineering, and product teams to understand requirements and constraints. Translate technical complexities into clear updates for leadership and ensure alignment on priorities and timelines.
- Process Improvement: Identify inefficiencies in current workflows and drive systematic improvements. Establish metrics and dashboards to track infrastructure health, capacity utilization, and deployment success rates.
You may be a good fit if you
- Have several years of experience in technical program management, with proven success delivering complex infrastructure programs, preferably in ML/AI systems or large-scale distributed systems
- Have deep technical understanding of inference systems, compilers, or hardware accelerators to engage substantively with engineers and identify technical risks.
- Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives
- Have strong stakeholder management skills and can build trust with both technical and non-technical partners
- Are comfortable navigating competing priorities and using data to drive technical decisions
- Have experience with infrastructure scaling initiatives, hardware integrations, or deployment governance
- Thrive in fast-paced environments and can balance strategic planning with tactical execution
- Are passionate about AI infrastructure and understand the unique challenges of deploying and scaling large language models
Deadline to apply: None, applications will be received on a rolling basis.
- 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.
