Senior Software Engineer, Ai/ml, AI and Infrastructure

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

Senior Software Engineer on the AI and Infrastructure team at Google, focusing on developing and scaling AI/ML capabilities and infrastructure for Google's products and customers. The role involves writing and testing code, collaborating on design and code reviews, triaging issues, and designing/implementing solutions in ML areas leveraging 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, and demonstrate expertise in a chosen field.

Skills

Required

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

Nice to have

  • 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

  • AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity
  • empower Google customers with breakthrough capabilities and insights
  • driving force behind Google's groundbreaking innovations
  • development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research