Founding Technical Partnerships Lead

About the role

This is a founding role at an early‑stage AI infrastructure company building data and evaluation tooling for the teams training the world’s most advanced AI models. You will serve as the primary bridge between the company and researchers and technical leaders at frontier AI labs, owning both the commercial relationship and the technical translation that makes those partnerships work.

Key responsibilities

• Build and manage relationships with researchers and technical leaders at frontier AI labs to understand their priorities and constraints.
• Identify technical needs across post‑training, evaluations, AI agents, and scientific data.
• Translate technical requirements from ML researchers into concrete dataset designs, experiments, and evaluation frameworks.
• Feed customer insights and feedback directly into the ML and experimental product roadmap.
• Define how the company engages with and scales partnerships with advanced AI teams.
• Own go‑to‑market strategy and positioning for partnerships with frontier research organizations.

Required profile

• 3 or more years in AI partnerships, business development, or research‑facing roles at AI labs, technical AI startups, or frontier research organizations.
• Demonstrated experience selling datasets or data products to frontier AI labs or comparable research organizations.
• Deep technical understanding of foundation models, post‑training methodologies, evaluation frameworks, and AI agents.
• Proven ability to translate technical ML researcher requirements into concrete dataset specifications, experimental designs, and evaluation protocols.
• Track record of identifying customer needs through technical discovery and converting them into commercial opportunities.
• Experience defining go‑to‑market strategies and commercial models for technical products or services.
• Comfort operating in early‑stage, ambiguous environments with minimal process and significant individual ownership.
• Prior experience at a frontier AI lab or advanced AI research organization is a strong plus.
• Background in machine learning research, ML engineering, scientific data generation, or laboratory automation is a plus.

Required skills

• Foundation models
• Post‑training methodologies
• Evaluation frameworks
• AI agents