Staff Software Engineer, Applied Ai, Search

Google Google · Big Tech · Bengaluru, Karnataka, India

Staff Software Engineer role focused on building Search for Commerce, including traditional search and agentic AI discovery experiences. The role involves developing scalable product search solutions and conversational agents for enterprises, leveraging ML infrastructure and collaborating with model builders.

What you'd actually do

  1. Design and implement solutions in one or more specialized ML areas and leverage ML infrastructure.
  2. Write and test product or system development code.
  3. 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.).
  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. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Skills

Required

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

Nice to have

  • ML infrastructure
  • model deployment
  • model evaluation
  • optimization
  • data processing
  • debugging
  • C++
  • technical leadership role

What the JD emphasized

  • experience in search, indexing or serving
  • 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.
  • experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Other signals

  • building scalable product search solutions
  • building conversational agents deployed at a large scale
  • leveraging ML infrastructure