Senior Software Engineer, Ai/ml, Google Cloud

Google Google · Big Tech · Sunnyvale, CA +1

Senior Software Engineer role focused on AI/ML within Google Cloud, working on AI and Infrastructure teams to deliver AI capabilities at scale. Responsibilities include writing and testing code, designing and implementing ML solutions, leveraging ML infrastructure, and triaging/debugging system issues. Requires experience in Python/C++, software development, and specific ML areas like speech/audio, reinforcement learning, or ML infrastructure.

What you'd actually do

  1. Write and test product or system development code.
  2. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
  3. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  4. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  5. Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure.

Skills

Required

  • Python
  • C++
  • Software development
  • Software design
  • Software architecture
  • Speech/audio technology
  • Reinforcement learning
  • ML infrastructure
  • Model deployment
  • Model evaluation
  • Optimization
  • Data processing
  • Debugging

Nice to have

  • Master's degree or PhD in Computer Science or related technical field
  • Data structures
  • Algorithms
  • Technical leadership
  • Accessible technologies

What the JD emphasized

  • 5 years of experience programming in Python or C++
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • 3 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.
  • 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Other signals

  • ML infrastructure
  • model deployment
  • model evaluation
  • optimization
  • data processing
  • debugging
  • Google Cloud
  • TPUs
  • Vertex AI