Engineering Manager, AI/ML Training Infra

Google•Sunnyvale, CA

3d•$207,000 - $300,000

About The Position

The Engineering Manager will lead a high-performing team of Software Engineers focused on designing, implementing, and launching critical scheduling features that support training and inference across Alphabet. The role supports internal customers and products including DeepMind, Google Search, YouTube, Ads, and Waymo, and partners with leadership and engineering teams across Compute infrastructure, SRE, Scheduling, XManager, Uniserve, and other infrastructure stakeholders to align technical roadmaps. The manager will shape the technical direction for next-generation scheduling infrastructure, balancing long-term architectural health with immediate business delivery needs. The role combines technical leadership and people management, including guiding engineers, managing project goals, contributing to product strategy, and developing the team. It also involves managing engineers across multiple teams and locations, a large product budget, and deployment of large-scale projects across international sites. The AI and Infrastructure team delivers AI and infrastructure capabilities at scale, efficiency, reliability, and velocity for Googlers, Google Cloud customers, and Google users worldwide.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience leading ML design and optimizing ML infrastructure, such as model deployment, model evaluation, data processing, debugging, or fine-tuning.
5 years of experience in speech/audio, reinforcement learning, or specialization in another ML field.
3 years of experience in a technical leadership role.
2 years of experience in people management or team leadership.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
Experience with distributed systems and a passion for building reliable, scalable, and efficient infrastructure.

Responsibilities

Set and communicate team priorities that support broader organizational goals, and align strategy, processes, and decision-making across teams.
Set clear expectations for individuals based on their level and role; meet regularly to discuss performance and development, and provide feedback and coaching.
Develop the mid-term technical direction and roadmap across one or more teams, evolving it to meet anticipated future requirements and infrastructure needs.
Design, guide, and vet system designs within the broader area, and write product or system development code to solve ambiguous problems.
Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide model optimization and data processing strategies.
Manage engineers across multiple teams and locations, a large product budget, and deployment of large-scale projects across multiple international sites.
Partner with internal customers and infrastructure stakeholders to drive aligned technical roadmaps for scheduling features supporting training and inference.