A growth-stage agentic risk platform dedicated to stopping financial crime.
Machine Learning Engineer
You are an engineer who sees fraud detection as a high-stakes contest of speed and intelligence, not just a data problem. In this role, you will build and deploy adaptive models that identify sophisticated threats in real-time across the global financial ecosystem. Your work directly protects billions in transactions by leveraging agentic AI to stay ahead of evolving criminal tactics.
What they're looking for
- 5 to 8 years of experience shipping production ML systems using Python, Go, and PyTorch.
- Deep expertise in designing low-latency inference pipelines within Kubernetes and Docker environments.
- Proven track record of applying Scikit-learn and deep learning techniques to cybersecurity or fintech challenges.
- Strong command of CI/CD practices to ensure reliable model deployment and monitoring at scale.