Staff Software Engineer, Search Ads ML and Large Language Models

Google Google · Big Tech · Pittsburgh, PA +1

Staff Software Engineer at Google working on Search Ads ML and Large Language Models. Responsibilities include designing, developing, testing, deploying, maintaining, and enhancing large scale software solutions, providing technical leadership, and leading the design and implementation of solutions in specialized ML areas, optimizing ML infrastructure, and guiding the development of model optimization and data processing strategies. Requires experience in software development, ML infrastructure, and ML design.

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. Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.

Skills

Required

  • software development
  • software design and architecture
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • ML design
  • model deployment
  • model evaluation
  • data processing
  • debugging
  • fine tuning

Nice to have

  • technical leadership
  • data structures
  • algorithms

What the JD emphasized

  • 8 years of experience in software development
  • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture
  • 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 with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)

Other signals

  • large scale software solutions
  • ML infrastructure
  • model optimization
  • data processing strategies
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • ML design
  • ML infrastructure