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Crucibl is building AI-powered judgment systems for enterprise clients, turning complex business decisions into faster, more defensible outcomes. The company is profitable, growing on revenue, and backed by Tier 1 VCs with a full client pipeline.
In this role, you'll design and build the reasoning and modeling components at the core of Crucibl's intelligence engine, including retrieval, orchestration, evaluation, and fine-tuning systems. You'll take promising ML research techniques and turn them into robust, production-grade systems that serve Fortune 500 clients.
Key responsibilities include:
- Designing and building core reasoning and modeling components for the intelligence engine
- Taking research techniques from prototype to production-grade systems
- Owning the full loop: experiment, measure, ship, iterate on real client data
- Building and improving models and pipelines that power enterprise judgment at scale
- Instrumenting systems to catch failure modes early and drive concrete improvements
- Balancing rigor with speed—clients need answers now
- Collaborating with founders on roadmap, trade-offs, and technical vision
- Shipping directly to enterprise clients with immediate, measurable impact
- Setting the bar for applied science excellence as the team grows
You must have at least one undeniable signal of excellence: shipped ML systems at a top tech company, early applied scientist at a startup that built something real, notable open source work, or top-tier CS/ML credentials. You need strong ML/AI fundamentals with proven ability to take models from prototype to production. You must have shipped meaningful ML-powered products end-to-end—not just features, but systems people rely on. Comfort with the full stack (data, modeling, evaluation, deployment) is essential.
Ideal candidates have experience building LLM-powered products, pipelines, or agentic systems in production; enterprise data systems or analytics infrastructure; operating in high-growth, high-ambiguity environments; and thinking like an owner with a big-picture perspective.
The company is not looking for scientists who need full specs before starting, coasters from large tech who maintained rather than shipped, or pure researchers without product instincts.
You'll work with founders who bring deep technology experience (Google-scale systems) and domain expertise in high-stakes business decisions from consulting and private equity. The role offers hybrid flexibility (3 days in-office), meaningful equity, full health coverage, and the opportunity to shape product, culture, and trajectory at a seed-stage company.
