Inference Optimization Manager

Modular•United States / Canada,

1d•$234,000 - $286,000•Remote

About The Position

At Modular, we optimize inference from kernel to cloud on one unified stack. We are building a differentiated cloud platform that delivers state of the art inference performance from day one, then keeps getting better. As we learn the shape and patterns of each customer's workload, the platform adapts and improves performance automatically over time. The Performance Labs team builds the infrastructure that makes this possible at scale. We continuously apply the latest optimizations across kernels, the inference engine, and distributed systems so that customer workloads stay on the Pareto frontier of cost and performance. We get there through deep workload insights, a scalable platform, and close collaboration with engineering and product teams. In this role you will lead a high impact team that partners closely with GTM, Product, and Engineering to redefine what an inference platform can be. You will turn real customer workloads into a continuous optimization loop, shape the product direction of Modular Cloud, and build the systems that let performance scale with demand.

Requirements

5+ years in distributed systems or performance engineering, including experience leading or managing engineering teams.
A track record of shipping durable, reusable software tools and libraries adopted across teams and functions, and of guiding a team to do the same.
Sound judgment in evaluating technical tradeoffs and setting priorities, paired with strong communication and technical leadership skills.
The ability to translate ambiguous customer and product needs into focused engineering direction.
Creativity and curiosity in solving complex problems, a collaborative and team oriented mindset, and alignment with our culture.

Nice To Haves

Hands on background in GPU kernel programming, inference engine internals, or distributed inference architectures.
Experience with Kubernetes and cloud native ecosystems.
Familiarity with modern LLM architectures and the latest inference optimization techniques.

Responsibilities

Lead the team that builds the optimization platform driving LLM inference on Modular Cloud to state of the art performance across the latest GPU and ASIC architectures.
Own the technical direction of Modular Cloud, delivering LLM performance on the Pareto frontier for agentic use cases and keeping it there as the landscape evolves.
Partner closely with the GTM team to deliver highly customized LLM inference tuned to specific customer workloads, and collaborate across engineering to drive optimizations spanning the full stack, from GPU kernels to cloud infrastructure. Translate insights from customer engagements into a clear technical roadmap that engineering teams can execute against.
Grow and develop a high impact team, set priorities, and create the conditions for engineers to do their best work on hard performance problems.
Champion the team externally through blog posts on innovative approaches to LLM inference optimization that shape industry wide best practices.