AI Infrastructure Engineer — Performance & Systems

Harrison Clarke

San Francisco (CA)

On-site

USD 180,000 - 260,000

Full time

6 days ago

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Job summary

Harrison Clarke is partnering with an early‑stage AI infrastructure company to hire a highly technical Machine Learning Engineer. This hands‑on role sits at the intersection of LLM systems, AI agents, inference and performance engineering, focusing on production workloads and system optimization.

You’ll contribute across AI infrastructure, agent systems, inference optimization, distributed execution and runtime performance, tackling bottlenecks and shaping the architecture as one of the first

Qualifications

Strong software engineering and computer science fundamentals.
Experience building complex production systems.
Depth in distributed systems, performance engineering, runtimes, databases, compilers, or AI infrastructure.
Meaningful experience with modern LLM or agent systems.
Ability to operate across multiple layers of the stack.
Comfortable in a highly ambiguous, early‑stage environment.

Responsibilities

Design and build infrastructure for production AI and agent workloads.
Improve the performance, efficiency and reliability of AI systems.
Work across inference, execution, runtime and distributed systems challenges.
Identify bottlenecks across complex production workloads and develop systems‑level solutions.
Build new infrastructure from first principles rather than simply integrating existing tools.
Help shape core technical architecture as one of the earliest engineers.