Google

Software Engineering Manager, GenAI Quality, Photos

Google Mountain View, California, United States · $207K–$300K/yr

Software Development · 10,001+ employees

4 h ago
engineering-manager Senior (5-10 yrs) Full-time United States
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About the role

The Software Engineering Manager will lead a team of engineers to drive technical excellence and quality in GenAI systems. They are responsible for project allocation, technical decision-making, and collaborating with product managers to align engineering efforts with product strategy.

What they look for

Software Development Machine Learning ML Infrastructure Technical Leadership GenAI Large Language Models Computer Vision People Management System Design Data Processing Model Deployment Model Evaluation Multimodal Models Product Strategy Cross-functional Collaboration

Requirements

Candidates must have at least 8 years of software development experience, including 5 years in ML infrastructure and 2 years in people management. A bachelor's degree is required, with a master's or PhD in a technical field preferred.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • 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 (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 3 years of experience in a technical leadership role.
  • 2 years of experience with GenAI techniques (e.g., large language models, multi-modal, large vision models) or with GenAI-related concepts (e.g., language modeling, computer vision).
  • 2 years of experience in a people management or team leadership role.

Preferred qualifications:

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 3 years of experience working in a complex, cross-functional organization.
  • Experience in launching ML enabled product features to public users.

About the job:

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

Photos Ellmann team's mission is helping users thrive by unlocking the full value of a life's worth of photos.

The Ellmann Signals and Modeling team builds out and refines signals and agentic tools to support Photos AI features and Google-wide Personal Intelligence. We use multimodal large language models (LLMs), classical machine learning, and LLM-assisted workflows for data and evaluation, and do tons of prototyping. We ship with standard Google infra for large-scale data processing and serving -- ps1, server platform, and flume.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Own the outcomes and technical decisions made by the team.
  • Drive engineering quality and technical excellence across all team deliverables.
  • Review technical designs and drive alignment for high-performing GenAI systems.
  • Identify and allocate projects according to team skillset, interests, and availability.
  • Collaborate with product managers to maximize quality for engineering effort and risk.

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