AI Benchmark Engineer: Onboard & Evaluate with Partners

DeepMind Technologies Limited; New York (NY); On-site; USD 174,000 - 232,000; Full time

Job summary

Google DeepMind is seeking a Forward Deployed Engineer on a 12-month fixed-term contract to join our benchmark onboarding efforts for Kaggle. You will collaborate with Engineering, Product, and Community teams to onboard external benchmarks and drive joint evaluations.

This role serves as the technical bridge between DeepMind’s partners and our model research teams, building evals, integrations, and producing insights to accelerate model improvements.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development and experience with coding in Python, JavaScript/TypeScript, or similar languages.
• 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.

Responsibilities

• Own the end to end onboarding of critical new benchmarks to the Kaggle platform.
• Drive joint evaluations and benchmarking, build and run systematic evals on partner-specific datasets to deliver high-fidelity performance signals directly to modeling teams.
• 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.

Skills

Software development

Python

JavaScript/TypeScript

ML systems / LLMs

Customer-facing

Education

Bachelor's degree or equivalent

Tools

APIs / SDKs

Benchmark tooling

Job description

Google DeepMind is seeking a Forward Deployed Engineer on a 12-month fixed-term contract to join our benchmark onboarding efforts for Kaggle. You will collaborate with Engineering, Product, and Community teams to onboard external benchmarks and drive joint evaluations.

This role serves as the technical bridge between DeepMind’s partners and our model research teams, building evals, integrations, and producing insights to accelerate model improvements.