Research Software Engineer

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

Research Software Engineer role focused on translating DeepMind's AI breakthroughs into AI/ML experiences for Google's Platforms and Devices (P&D) initiatives. The role involves architecting solutions, guiding product teams from concept to launch, and leading the end-to-end development of AI features, with a focus on shipping AI/ML products to billions of users. Requires experience with LLMs, NLP, and ML infrastructure, with a strong emphasis on building scalable ML infrastructure and leading technical architecture.

What you'd actually do

  1. Oversee the end-to-end technical architecture and drive technical consensus across teams.
  2. Design high-level systems and build scalable, reusable ML infrastructure that serves as a foundation for multiple product teams.
  3. Establish the standard for engineering excellence by steering architectural reviews, mentoring engineers on system design, and identifying strategic opportunities to accelerate innovation across the entire Platforms and Devices ecosystem.
  4. Cultivate deep partnerships with product teams and researchers at DeepMind, serving as the primary technical voice and engineering liaison for the team, while translating state-of-the-art AI research into tangible user experiences in products by guiding engineers through integrations, resolving technical ambiguities, and aligning cross-functional stakeholders on a unified technical goal.
  5. Lead the end-to-end development of AI features by orchestrating the team's engineering efforts under tight, high-visibility deadlines.

Skills

Required

  • Software development
  • Speech/audio technology
  • Reinforcement learning
  • ML infrastructure
  • Large Language Models
  • Natural Language Processing
  • Software design and architecture
  • System design

Nice to have

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field
  • Data structures and algorithms
  • Technical leadership
  • Cross-functional project experience

What the JD emphasized

  • translate the latest breakthroughs from DeepMind into AI/ML experiences
  • architecting solutions and directly guiding product teams from concept to launch
  • building innovative experiences for our users around the world
  • Experience with Large Language Models
  • Experience with Natural Language Processing
  • speech/audio
  • reinforcement learning
  • ML infrastructure

Other signals

  • Translating AI research into user experiences
  • Shipping AI/ML features
  • Building scalable ML infrastructure
  • Guiding product teams from concept to launch