About the role
Why you should join us
- We are building an autonomous factory for financial service agents, with real-time feedback loops from some of the largest financial services companies in the world, our customers.
- We work with structured and unstructured data at scale including calls, chats, emails, and AI agent responses to build autonomous systems that adapt, detect, and act on customer interactions in real time.
- Our edge is not secret datasets or brute-force compute. It is the speed at which we iterate, deploy, and learn directly from live environments.
- You will lead ML/AI strategy at the intersection of cutting-edge research and real-world deployment in regulated industries.
What you’ll do
- Lead the development of reinforcement learning (RL) agents and autonomous agents designed for financial services.
- Build systems that automatically review 100% of customer interactions across voice, chat, email, and AI agents to flag compliance risks, fraud attempts, and operational gaps in real time.
- Architect autonomous workflows with built-in compliance requirements.
- Develop safe-guarded AI decisioning that blends automation with judgment-based escalation paths, ensuring AI is auditable, explainable, and regulator-ready.
What we’re looking for
- Deep expertise in ML and AI, especially NLP, anomaly detection and representation learning for unstructured text and audio.
- Strong coding background in Ruby or Python, with experience in data pipelines, AWS or GCP infrastructure, and orchestration frameworks.
- Experience deploying production-ready AI agents or automation systems. You care about what works in the real world, not just what looks good on paper.
- Background in financial services or compliance-sensitive systems is a plus, but not required. Curiosity and rigor matter more.
