Senior Staff Software Engineer, Ai/ml, Google Cloud

Google Google · Big Tech · Seattle, WA +1

Senior Staff Software Engineer on the AI and Infrastructure team at Google Cloud, focusing on delivering AI and Infrastructure at scale. The role involves designing, developing, and deploying large-scale software solutions, providing technical leadership, and driving ML infrastructure optimization across multiple ML areas. Requires extensive experience in ML infrastructure, design, architecture, and specific ML fields like speech/audio or reinforcement learning.

What you'd actually do

  1. Design, develop, test, deploy, maintain, and enhance large scale software solutions.
  2. Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
  3. Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
  4. Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.

Skills

Required

  • Software development
  • Technical project strategy
  • ML design
  • ML infrastructure optimization
  • model deployment
  • model evaluation
  • data processing
  • debugging
  • fine tuning
  • design and architecture
  • testing/launching software products
  • Speech/audio technology
  • reinforcement learning
  • ML infrastructure
  • specialization in another ML field

Nice to have

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • data structures/algorithms
  • technical leadership role leading project teams and setting technical direction
  • working in a complex, matrixed organization involving cross-functional, or cross-business projects.

What the JD emphasized

  • 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 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.

Other signals

  • ML infrastructure optimization
  • model deployment
  • model evaluation
  • data processing
  • fine tuning
  • Speech/audio
  • reinforcement learning