Software Engineer

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

Software Engineer at Google DeepMind focused on applying research to high-impact problems by prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning. The role involves developing and testing robust product code, collaborating with peers, triaging issues, creating documentation, and managing the full deployment lifecycle.

What you'd actually do

  1. Apply research to high-impact problems by prototyping GenAI solutions, curating datasets, and building ML pipelines for generative media, multimodal understanding, and reinforcement learning
  2. Develop and test robust product code, performing comprehensive testing that includes integration, performance, and security to ensure system quality and reliability
  3. Collaborate with peers through rigorous design and code reviews to enforce best practices, improve system testability, and ensure overall efficiency and accuracy
  4. Triage and resolve complex system issues by debugging, analyzing root causes, and implementing solutions to optimize hardware, network, and service operations
  5. Create and maintain technical documentation and educational materials, adapting content based on product updates and user feedback to ensure clarity and relevance

Skills

Required

  • Software development using Java, C, C++, Python, Go, Kotlin or Typescript
  • Designing and applying data structures or algorithms
  • Systems thinking or analyzing technical problems from a broad, systems-level perspective
  • Web frontend development on a modern framework such as React or Angular
  • Software testing, including unit and integration tests
  • Bachelor’s degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Physics or a related field and 2 years of experience in the job offered or in a Software Engineer-related occupation

Nice to have

  • prototyping GenAI solutions
  • curating datasets
  • building ML pipelines
  • generative media
  • multimodal understanding
  • reinforcement learning
  • integration testing
  • performance testing
  • security testing
  • debugging
  • technical documentation

What the JD emphasized

  • prototyping GenAI solutions
  • building ML pipelines
  • generative media
  • multimodal understanding
  • reinforcement learning
  • Software development using Java, C, C++, Python, Go, Kotlin or Typescript
  • Designing and applying data structures or algorithms
  • Systems thinking or analyzing technical problems from a broad, systems-level perspective
  • Software testing, including unit and integration tests

Other signals

  • prototyping GenAI solutions
  • building ML pipelines
  • generative media
  • multimodal understanding
  • reinforcement learning