Create roadmaps for developer-facing APIs, SDKs, and tools, ensuring they meet the evolving needs of LLM workflows.

Solve technically challenging problems that exceed the scope of a generalist Software Engineers, specifically around optimizing GenAI performance across heterogeneous hardware (CPUs, GPUs, and EdgeTPUs).

Guide the team in designing resilient and systems, anticipating scaling bottlenecks or shifts in usage as LLMs become increasingly complex.

Coordinate efforts across multiple groups, including Android ML, ML Compiler, and Deep Mind, to co-design performance and evaluation workflows.

Provide technical mentorship, and implement new practices that address team needs and increase the velocity of your teammates.

Bachelor’s degree or equivalent practical experience.

8 years of experience in software development.

5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.

5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.

5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).