Engineering Manager, ML Efficiency at Google

Seniority in posting: Advanced

Compensation

$207,000 – $300,000/yr

Location: Mountain View, California
Type: Full-time
Level: lead/mgmt
Posted: Sep 4, 2026

Description

Google is hiring an Engineering Manager on the ML Efficiency team to lead technical architecture and engineering management for AI/ML systems engineers. The role balances deep technical contributions with strategic pod leadership, including Strike Sprints, Forward Deployed Engineering teams, model distillation, speculative decoding, dynamic batching, distributed serving, legacy pipeline modernization, and high-stakes technical feasibility work. The position requires a bachelor’s degree or equivalent practical experience, 8 years of software development experience, and extensive experience in software products, software design and architecture, and ML infrastructure. Compensation is $207,000–$300,000 USD plus a 20% bonus target, equity, and benefits.

Required Skills

C++
Python
System design
Model distillation
Speculative decoding
Distributed serving
ML infrastructure
Generative AI

Additional Information

Minimum Education: Bachelor’s degree or equivalent practical experience
Required Previous Experiences: 8 years of software development experience
5 years of software product testing and launch experience
3 years of software design and architecture experience
5 years of experience in speech/audio, reinforcement learning, ML infrastructure, or another ML field
5 years of ML design and ML infrastructure experience
Experience integrating generative AI tools or LLM interfaces into workflows
Preferred Qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field
8 years of polyglot C++ and Python coding expertise and familiarity with Google core infrastructure
8 years of experience with data structures and algorithms
3 years of experience in a complex, matrixed organization with cross-functional or cross-business projects
Knowledge of bridging high-velocity prototyping with permanent distributed enterprise scale through structured handoff packages
Track record leading SWAT, Pathfinding, or Forward Deployed Engineering teams in fast-paced startup or ambiguous enterprise environments