Forward Deployed Engineer, Kaggle

About the job

Our team works at the intersection of Engineering, Product, and Community. You will work in the emerging benchmark ecosystem to onboard external benchmarks to Kaggle. Through collaborative engineering, joint benchmarking, and feedback loops, we run systematic evaluations to accelerate model capability understanding.

The Forward Deployed Engineer is the technical bridge between DeepMind’s most strategic partners and our model research teams. This role is embedded in the partner’s engineering journey, building joint evals, unblocking complex integrations, and synthesizing deep technical signals to drive model improvements.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $232000 (USD) + 15% bonus target

Learn more about benefits at Google.

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.

Qualifications

Minimum 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.

Preferred qualifications:

• Experience building public benchmarks and evals.
• 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.