Software Engineering Manager, AI/ML, Google Labs

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.

Labs is a group focused on incubating early-stage efforts in support of Google’s mission to organize the world’s information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer timeframes.

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

• 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 the multiple teams. 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 write product or system development code to solve ambiguous problems.
• Lead the design and implementation of solutions in specialized Machine Learning (ML) areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.

Qualifications

• Minimum qualifications:
  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • 5 years of experience leading ML design and optimizing end-to-end machine learning (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.