Principal Machine Learning Engineer
Core
Lead the engineering build-out of ML and agentic AI systems for AML/KYC and Fraud platforms, extracting entities and risks to power a real-time financial crime knowledge graph.
Role type
Principal Machine Learning Engineer (Senior IC + Architectural Leadership)
Builds
Company-wide MLOps and agentic AI platforms, new models, and agent systems for financial crime detection
Domain
Financial Crime (AML/KYC/Fraud) + Machine Learning & Agentic AI
Deliverable
production ML models
Required skills
Large language model (LLM) engineering, MLOps platform architecture, Python software engineering, cloud infrastructure (AWS/GCP), event-driven architectures, mathematical/statistical foundations, CI/CD pipeline design, Kubernetes/Docker, Kafka, graph neural networks
Preferred skills
Knowledge graph design, entity resolution, LLM evaluation frameworks, public speaking at conferences
Technologies
Python, Kotlin, TypeScript, React, Postgres, Yugabyte, Kafka, gRPC, Grafana Cloud, ArgoCD, AWS, GCP, Kubernetes, Docker
Responsibilities
Architect company-wide MLOps and agentic AI platforms; translate data science roadmaps into scalable engineering deliverables; set engineering standards for code quality and operational rigor; lead end-to-end build-out of AI systems including RAG and multi-agent systems; coach ML engineers and improve hiring processes
Seniority
Principal, hands-on IC with strategic execution and mentorship
