Founding Applied AI/ML Engineering

About the role

This is a rare opportunity for a hands-on builder to work across the full product stack, build 0 to 1 and grow with a young team. We're looking for a Founding AI/ML Engineer who is passionate about solving challenging problems in a highly regulated industry. You don't have to know FDA or biotech, but you believe in vertical AI solutions and want to push the boundary of what is possible.

Backed by top-tier investors from Applied AI and infra, with advisors from GitHub, OpenAI, and Mercor.

You get market standard comp, equity, viable path to Head of Engineering or beyond.

You will work closely with 2 engineers on the team, build, ship quickly and shape our product vision.

You'll work on the full production pipeline including data pipeline, database, RAG, multi-agent orchestration, eval benchmarks for internal agent performance and frontier model benchmarking.

You'll work with diverse data sources and cross-domain with experts to translate domain knowledge into structured databases.

Key responsibilities

1. Build & Ship: Own architectural decisions that balance innovation, scalability, cost, and long-term maintainability in a high-stakes domain.
2. Ingest at Scale: Build robust, scalable pipelines to ingest, extract, and structure heterogeneous regulatory sources into training- and retrieval-ready datasets.
3. Data Quality: Ensure data quality, provenance, versioning, and governance across the corpus, with automated validation and monitoring.
4. Benchmark & Evals: Build datasets, define rigorous metrics, and measure model performance across high-impact AI tasks to guide development.
5. Human Annotations: Build scalable pipelines to collect structured human feedback, benchmark subjective quality, and inform model iterations.
6. Product Partnership: Partner with the founding team on product vision and challenge assumptions.

Who you are

1. Cracked: You love to build.
2. Strong opinions: You have strong opinions and product taste, and you're not afraid of pushing back.
3. Real-World Experience: You have experience building data pipelines, ML infrastructure, and have shipped products in previous startups or projects.
4. Execution-Oriented: You move fast, take ownership, and focus on solving real problems.
5. Clear Communicator & Team Player: You collaborate well across functions and push decisions forward.

Interview process

1. 30min intro with CEO & cofounder
2. 40min tech call where you meet our engineering team
3. Short paid take-home (~5hr) for mutual evaluation

Decision in 2 weeks. Don't miss this rare opportunity to define the next generation of medicine approvals.

We hope to hear from you.