Senior Staff Data Scientist - AI
Ironclad · San Francisco, CA · Engineering, Product & Design
About this role
Ironclad is hiring a senior-level Data Scientist based in San Francisco, CA. The posting calls out experience with LLMs, Reinforcement Learning, System Design, AI Agents. Compensation is listed at $245,000–$295,000 per year.
- Role
- Data Scientist
- Function
- data engineering
- Level
- senior
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- Engineering, Product & Design
- Posted
- Apr 28, 2026
More roles at Ironclad
Job description
from Ironclad careersIronclad is the leading AI contracting platform that transforms agreements into assets. Contracts move faster, insights surface instantly, and agents push work forward, all with you in control. Whether you’re buying or selling, Ironclad unifies the entire process on one intelligent platform, providing leaders with the visibility they need to stay one step ahead. That’s why the world’s most transformative organizations, from Rivian to the World Health Organization and the Associated Press, trust Ironclad to accelerate their business.
We’re consistently recognized as a leader in the industry: a Leader in the Forrester Wave and Gartner Magic Quadrant for Contract Lifecycle Management, a Fortune Great Place to Work, and one of Fast Company’s Most Innovative Workplaces. Ironclad has also been named to Forbes’ AI 50 and Business Insider’s list of Companies to Bet Your Career On. We’re backed by leading investors including Accel, Y Combinator, Sequoia, BOND, and Franklin Templeton. For more information, visit www.ironcladapp.com or follow us on LinkedIn.
About the Role
Ironclad is accelerating its investment in AI to redefine how legal teams manage and understand contracts. As part of this effort, we are hiring an AI Evaluation Engineer to work within our AI Pillar. This role is focused on unlocking insights from our training data, designing feedback loops, and ensuring the continuous improvement of our agentic and ML or LLM-based systems through data-driven evaluation and iteration.