Applied Scientist

About the role

Why Blee:

Blee is an AI-first marketing content compliance platform. PayPal, NerdWallet, and Brex already trust us. We're YC-backed, founded by an ex-Adobe marketing ops leader and former lawyer, and we're defining a category that didn't exist two years ago—across Fintech, Financial Services, CPG, Travel, and Life Sciences..

With offices in San Francisco and New York, we value in-person work but offer remote-opportunities for the right people. No matter where you join us, you can expect quarterly off-sites and opportunities to join other offices when you feel it’s important. You’ll be joining a team that values clarity, ownership, and shared responsibility—and is focused on building something that genuinely improves how teams work.

The Role

This is an Applied Scientist role specializing in agent system design for someone who wants to architect and implement the next generation of intelligent compliance systems. You will design frameworks where multiple agents—powered by custom and foundational models—work together to surface, track, and explain compliance flags. You will also build and optimize applied AI/ML pipelines, work across model fine-tuning, prompt engineering, evaluation frameworks, and customer-specific AI configurations, and train models based on user feedback to provide more targeted compliance recommendations.

What You'll Do

- Architect multi-agent systems – Design and implement frameworks that integrate foundational LLMs and custom-trained models to power intelligent compliance workflows

- Build and optimize AI/ML pipelines – Model fine-tuning, prompt engineering, and evaluation frameworks

- Ensure explainability and traceability – Build mechanisms for transparent flagging, ensuring every compliance flag is traceable to prior rules, examples, or data assets

- Automate compliance rule translation – Build systems that transform compliance rules into agent-ready logic paths

- Design, train, and fine-tune models – Improve compliance accuracy and adaptability using user feedback and outcomes data to drive iterative training and personalization

- Design model evaluation and monitoring infrastructure – Ensure reliability and auditability across customer deployments

- Collaborate cross-functionally – Work with Product Engineers to integrate AI features via APIs, data pipelines, and frontend; partner with model training engineers to incorporate feedback loops into system design; collaborate with compliance users to translate complex rules into agent workflows

- Stay current on AI/ML advances – Prototype and apply new techniques to our platform

Who You Are

- Deeply technical and hands-on – you love building production ML systems, not just prototyping

- Customer-outcome oriented – you care about how your models perform in the real world, not just on benchmarks

- A fast learner who thrives at the intersection of AI and domain-specific problems, especially compliance and governance