Forward Deployed Engineer, DeepMind

Qualifications

• Bachelor's degree or equivalent practical experience.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• Experience with Machine Learning systems or Large Language Models (LLMs).
• Experience in a customer‑facing role, managing client relationships or external stakeholders.

• Experience working with developer tools, APIs, SDKs, or platform integration.
• Ability to collaborate directly with external customers or partners in a technical capacity.
• Ability to work independently with minimal oversight across global time zones.
• Excellent technical writing and communication skills, along with the ability to produce documentation, tutorials, or engineering case studies.

The team works at the intersection of Engineering, Product, and Community. We advocate partner success and model excellence by embedding with Deep Mind’s most strategic developers. Through collaborative engineering, joint benchmarking, and feedback loops, we run systematic evaluations to accelerate model improvements, unblock key integrations, and showcase Gemini’s capabilities at scale.

As a Forward Deployed Engineer (FDE), you will serve as the technical bridge between Deep Mind’s model teams and our most strategic partners. Embedded directly in the partner’s engineering journey, you will design joint evaluations, unblock complex integrations, and synthesize high‑fidelity technical signals to directly influence model development. This role demands a combination of technical expertise, customer empathy, and the autonomy to operate effectively across global time zones.

• 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.
• Drive joint evaluations and benchmarking, build and run systematic evals on partner‑specific datasets to deliver high‑fidelity performance signals directly to modeling teams.
• Optimize GenAI workloads, guide partners on advanced implementation techniques, including prompt engineering, complex Retrieval‑Augmented Generation (RAG) architectures, and multimodal integrations.
• Author high‑visibility case studies, developer blogs, and reference implementations to showcase Gemini’s production capabilities.
• Build feedback loop tooling, collaborate with product engineering to develop tooling that aggregates and surfaces developer feedback patterns at scale.

US: $174,000 - $253,000 (USD) + 15% bonus target + equity + benefits.

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