Forward Deployed Engineer, Deepmind

Google Google · Big Tech · Mountain View, CA +3

This role serves as a technical bridge between DeepMind's model teams and strategic partners, focusing on embedding with partners to architect, optimize, and build production-grade GenAI applications. The FDE will drive joint evaluations, unblock integrations, and optimize GenAI workloads, influencing model development through synthesized technical signals and feedback loops.

What you'd actually do

  1. Embed with strategic partners, own the technical relationship with top strategic partners, helping them architect, optimize, and build production-grade GenAI applications. Serve as the primary technical escalation path for strategic partners during critical launch windows and production issues.
  2. Drive joint evaluations and benchmarking, build and run systematic evals on partner-specific datasets to deliver high-fidelity performance signals directly to modeling teams.
  3. Optimize GenAI workloads, guide partners on advanced implementation techniques, including prompt engineering, complex Retrieval-Augmented Generation (RAG) architectures, and multimodal integrations.
  4. Author high-visibility case studies, developer blogs, and reference implementations to showcase Gemini's production capabilities.
  5. Build feedback loop tooling, collaborate with product engineering to develop tooling that aggregates and surfaces developer feedback patterns at scale.

Skills

Required

  • software development
  • Python
  • JavaScript/TypeScript
  • software design and architecture
  • Machine Learning systems
  • Large Language Models (LLMs)
  • customer-facing role
  • managing client relationships
  • external stakeholders

Nice to have

  • developer tools
  • APIs
  • SDKs
  • platform integration
  • technical capacity
  • work independently
  • technical writing
  • communication skills
  • documentation
  • tutorials
  • engineering case studies

What the JD emphasized

  • production-grade GenAI applications
  • systematic evaluations (evals)
  • high-fidelity technical signals
  • Gemini's capabilities at scale
  • Gemini's production capabilities

Other signals

  • customer-facing role
  • technical bridge between DeepMind's model teams and our most strategic partners
  • design joint evaluations
  • unblock complex integrations
  • synthesize high-fidelity technical signals to directly influence model development