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Staff Software Engineer, AI/ML GenAI, Google Cloud Applications AI

Google

$197,000 - $291,000
Sep 12, 2025
Sunnyvale, CA, US
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Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

Requirements

  • 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).
  • 5 years of experience testing, and launching software products.
  • 3 years of experience with software design and architecture.
  • 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
  • 8 years of experience with data structures/algorithms.
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.

Responsibilities

  • Design, develop, test, deploy, maintain, and enhance large scale software solutions.
  • Provide technical leadership on high-impact projects.
  • Manage project priorities, deadlines, and deliverables.
  • Lead the design of GenAI solutions, optimize ML infrastructure, and guide the development of data preparation and model optimization strategies.

Other

  • Bachelor’s degree or equivalent practical experience.
  • 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.
  • Facilitate alignment and clarity across teams on goals, outcomes, and timelines.
  • Influence and coach a distributed team of engineers.