Software Engineer, Ai/ml, Google Research

Google Google · Big Tech · Mountain View, CA +1

Software Engineer role at Google Research focusing on implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing. Requires experience in specialized ML areas like speech/audio, reinforcement learning, or ML infrastructure, with a focus on model deployment, evaluation, optimization, and data processing.

What you'd actually do

  1. Write 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. Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

Skills

Required

  • software development
  • programming languages
  • Speech/audio
  • reinforcement learning
  • ML infrastructure
  • model deployment
  • model evaluation
  • model optimization
  • data processing
  • debugging

Nice to have

  • data structures
  • algorithms
  • accessible technologies

What the JD emphasized

  • 1 year 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.
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Other signals

  • Implement solutions in one or more specialized ML areas
  • utilize ML infrastructure
  • contribute to model optimization and data processing
  • 1 year of experience with one or more of the following: Speech/audio
  • reinforcement learning
  • ML infrastructure
  • specialization in another ML field
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging)