Founding Engineer - Research
You'll work with Python, modern ML tooling, LLMs, and simulations, owning the AI/ML stack including model selection, fine-tuning, and inference infrastructure. Prior Foundry builds specialized AI agents and inference systems to solve complex global policy problems for the public sector in social science and public policy.
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Job Title
Founding Engineer - Research
Salary
Not Disclosed + Equity
Company Description
Prior Foundry is a research-led technology company extending the frontier of simulations and Large Language Models within the fields of social science and public policy. Operating across London and NYC, the team builds specialized AI agents and inference infrastructure to solve complex global policy problems for the public sector.
Job Description
Join Prior Foundry as a Founding Research Engineer to bridge the gap between applied research and production systems. You will lead efforts in benchmarking simulations on policy problems, building specialized agents for economic analysis, and owning the end-to-end AI/ML layer. This role is pivotal in shaping how simulations impact real-world governance and social sciences.
Location
London, UK or New York, USA
Why this role is remarkable
Sit at the intersection of cutting-edge LLM research and tangible public sector impact, solving high-stakes problems in social and economic policy.
High-autonomy founding role with considerable equity upside and the opportunity to influence the core architecture of a scaling research-led company.
Experience a unique global culture with regular travel between Paris, London, and NYC, working directly with users to ground your research in reality.
What You Will Do
Lead the benchmarking of advanced simulations on new policy problems across diverse fields like econometrics and causal inference.
Build and deploy specialized research agents and production-grade data pipelines to support complex social and economic policy workflows.
Own the entire AI/ML stack, including model selection, fine-tuning, inference infrastructure, and the continuous feedback loops that drive model improvement.
The ideal candidate
Possesses 2–3 years of experience building ML systems in production or conducting deep applied research in ML or statistical domains.
Demonstrates strong proficiency in Python and modern ML tooling, with a proven track record of moving from research ideas to working systems.
Combines a genuine interest in public sector problems with the ability to navigate ambiguity and sparse specifications in a startup environment.