Job Description
In most instances, this position requires in-person interviews as part of the hiring process.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.Minimum qualifications:
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.Minimum qualifications:
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
- 5 years of experience with one or more general purpose programming languages including but not limited to: Java, C/C++, Python, Objective C, JavaScript, or Go.
- Experience building or integrating Large Language Model (LLMs), generative AI models, or ML-powered systems into production applications.
- Experience with partner management, cross-functional teams, and leading operational initiatives.
- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- 3 years of experience launching and managing technical, developer-facing products such as Application Programming Interfaces (APIs), Software Development Kits (SDKs), or platforms.
- Extensive working knowledge of modern AI/ML architectures, including LLM evaluations, Retrieval-Augmented Generation (RAG), and agentic workflow designs.
- Ability to effectively communicate compelling vision, architecture and complex technical concepts.
US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Responsibilities
Learn more about benefits at Google .
- Manage the technical relationship for AI Futures Fund portfolio partners, guiding the architecture of production-grade generative AI applications and ensuring partner feedback directly impacts model development.
- Design, build, and execute systematic evaluations on partner-specific datasets and real-world workloads to provide DeepMind research teams with high-fidelity performance signals.
- Partner closely with model teams on custom evaluation design, auto-rater setup, and validation to contribute directly to Gemini checkpoint training and active tuning.
- Author high-visibility technical case studies, code samples, and developer deep-dives highlighting breakthrough AIFF partner use cases and demonstrating Gemini’s performance in production.
- Collaborate with Google Labs, Cloud, Developer Relations teams to ensure AIFF technical learnings, best practices, and ecosystem wins scale across Google.
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