Staff Software Engineer, Ai/ml, Contextual Suggest

Google Google · Big Tech · Belo Horizonte, State of Minas Gerais, Brazil +1

Staff Software Engineer at Google working on AI/ML for Contextual Suggest, focusing on recommendation systems, ML infrastructure, and integrating AI breakthroughs into user-facing features and backend systems for Google Search. The role involves technical leadership, design, implementation, and deployment of models in production.

What you'd actually do

  1. Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
  2. Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
  3. Lead the design and implementation of recommendation systems, optimize ML infrastructure, and guide the development of model architecture.
  4. Research signals, engineering, quality analysis, experimentation, evaluation methods to develop high-impact, user-facing features that leverage new AI breakthroughs.
  5. Develop scalable backend systems that integrate with Suggest, AI Mode and the informational agent API.

Skills

Required

  • software development
  • software products
  • software design and architecture
  • recommendation systems models (retrieval, prediction, ranking, embedding) in production
  • architecture in different modeling domains
  • ML design
  • ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)

Nice to have

  • technical leadership
  • data structures and algorithms
  • complex, matrixed organization
  • cross-functional, or cross-business projects

What the JD emphasized

  • recommendation systems models (retrieval, prediction, ranking, embedding) in production
  • ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)

Other signals

  • recommendation systems
  • ML infrastructure
  • user-facing features
  • AI breakthroughs
  • backend systems