Engineering Manager, ML Efficiency & AI Rapid Response

Google Inc.; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google Inc. is seeking an Engineering Manager for ML Efficiency on the AI Rapid Response Team. You will balance deep technical contributions with strategic leadership, guiding a high-performing team across multiple sites and complex projects.

You will drive architecture for large-scale ML pipelines, lead Sprints, and collaborate with leadership to shape product strategy and engineering culture. Strong C++/Python skills and ML infra expertise are essential.

Qualifications

• 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, reinforcement learning, ML infrastructure, or related ML field.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Experience integrating generative AI tools or LLM interfaces into workflows.

Responsibilities

• Lead technical pathfinding and system design for ML Efficiency Hub, driving complex 1–6 month projects and 2–4 week Sprints.
• Design, prototype, and write production C++ and Python code for model distillation and distributed serving systems.
• Take high-stakes VP-level efficiency mandates and de-risk feasibility within latency, FLOPs, and token limits.
• Establish concrete handoff packages to ensure partner teams achieve permanent autonomy.

Skills

C++

Python

ML infrastructure

Distributed systems

Pathfinding

Education

Bachelor’s degree

Master’s degree or PhD (preferred)

Tools

XManager

BrainServer

SavedModel

Pathways

Job description

Google Inc. is seeking an Engineering Manager for ML Efficiency on the AI Rapid Response Team. You will balance deep technical contributions with strategic leadership, guiding a high-performing team across multiple sites and complex projects.

You will drive architecture for large-scale ML pipelines, lead Sprints, and collaborate with leadership to shape product strategy and engineering culture. Strong C++/Python skills and ML infra expertise are essential.