Software Engineering Manager, Cloud AI/ML Infrastructure

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.

Google welcomes people with disabilities.

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 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, matrixed organization involving cross-functional, or cross-business projects.
• Experience with Generative AI, Large Language Models (LLMs), or Machine Learning infrastructure, including model deployment, performance optimization, profiling, and debugging.
• Experience with distributed computing leveraging Graphics Processing Units (GPUs) or Tensor Processing Units (TPUs).
• Ability to solve ambiguous problems, and grow in a dynamic, changing environment where AI technologies are continuously advancing.

Responsibilities

• Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  
• Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
  
• Develop the mid-term technical goal and roadmap within the scope of your team. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
• Design, guide, and vet systems designs within the scope of the broader area, and partner closely with cross-functional, cross-regional teams to ensure our AI/ML infrastructure delivers exceptional value and drives success for our customers.
• Lead the design and development of tools and software for our AI/ML Infrastructure to deliver end-to-end developer experience.