Software Engineering Manager, GenAI, Computer Vision, Google Maps Immersive Navigation

Google

Mountain View, CA, United States1mo ago

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Key details

Salary
$207K–$300K/yr
Location
Mountain View, CA, United States
Work style
Onsite
Level
Senior
Experience
8–11 yrs
Function
Data & ML
Focus area
AI / ML
Posted
1mo ago

Skills

algorithmsc++code reviewscomputer visiondeep learningdistributed computinggenerative aijavajavascriptmachine learningmodel deploymentmodel evaluationnatural language processingnetworkingproduct strategypythonreinforcement learningtensorflow

About the role

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.

The Geo team is embarking on a multi-year journey to build and scale the newly announced 3D Immersive Navigation Experience.

As an Engineering Manager, you will use your extensive Machine Learning and Computer Vision experience to lead the team in designing and building the freshest and most detailed 3D navigation map using sensor data (e.g., imagery, vehicle telemetry, location data, authoritative data, etc.), large ML models, and AI techniques to create new structured geospatial data and transformative user experiences for 2 billion+ users globally.
The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.

The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.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

  • Take end-to-end ownership of converting complex imagery, location, and sensor data into precise geometries to power Geo’s next generation navigation products. Translate ambiguous input data challenges into clear algorithmic, ML, GenAI formulations, brainstorming directly with product, UX, and engineering to define the optimal visual experience and iterate towards scalable solutions.
  • 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, aligned with broader organizational goals. Meet regularly with individuals to discuss performance, development, feedback and coaching.
  • Develop the long-term technical outlook and roadmap, meeting anticipated future requirements and infrastructure needs.
  • Design, guide and vet system designs, and write product or system development code to solve ambiguous problems. Conduct code reviews and provide feedback ensuring best practices.

Minimum qualifications:

  • Bachelor’s degree, or equivalent practical experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 5 years of experience in a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role.
  • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or a related technical field.
  • 5 years of experience with one or more of the following: Computer Vision, Reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • Multiple research publications in top CV/ML conferences (e.g., CVPR/ICCV/ECCV/NIPS/ICLR).
  • Experience working in large-sized engineering and cross-functional teams.
  • Expertise in modeling with TensorFlow, JAX, etc.
  • Excellent people management and communication skills.
  • Bachelor’s degree, or equivalent practical experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 5 years of experience in a technical leadership role; overseeing projects, with 3 years of experience in a people management, supervision/team leadership role.
  • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • Experience with computer vision learning techniques, machine learning algorithms (supervised and unsupervised learning, deep learning, reinforcement learning), generative AI, or applied AI applications
In most instances, this position requires in-person interviews as part of the hiring process.

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