Senior Software Engineer, Ai/ml, Google Cloud AI

Google Google · Big Tech · Sunnyvale, CA +1

Senior Software Engineer role focused on AI/ML within Google Cloud AI. The role involves designing and implementing solutions in specialized ML areas, leveraging ML infrastructure, and contributing to product/system development. Key areas include speech/audio, reinforcement learning, ML infrastructure, model deployment, evaluation, optimization, data processing, and debugging.

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, and demonstrate expertise in a chosen field.

Skills

Required

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

Nice to have

  • Master's degree
  • PhD
  • Computer Science
  • 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
  • Speech/audio
  • reinforcement learning