Senior/Staff Machine Learning Engineer
Core
Building and deploying machine learning systems and LLM-based agents for fraud detection, risk management, and operational workflows at a global crypto exchange.
Role type
Senior/Staff Machine Learning Engineer (Risk & AI Agents)
Builds
Production ML models and AI-powered risk control systems for a crypto exchange
Domain
Cryptocurrency / Financial Risk / AI Engineering
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, XGBoost, LightGBM, scikit-learn, supervised learning, anomaly detection, representation learning, class-imbalanced modeling, model calibration, LLM coding tools, agentic workflows, tool calling, retrieval-augmented generation, prompt management, structured output generation, multi-step task orchestration
Preferred skills
Model explainability (SHAP, feature attribution), LLM-agent evaluation (hallucination control, grounding), integrating agents with internal systems/APIs, experience in fraud/risk/compliance domains
Technologies
PyTorch, TensorFlow, XGBoost, LightGBM, scikit-learn
Responsibilities
Design, build, and deploy ML models for payment fraud, account takeover, scam detection, and transaction monitoring; Own production ML systems end-to-end including feature pipelines, model serving, and monitoring; Partner with risk strategy to translate models into production controls; Work with operations to refine labels and improve model explainability; Apply AI-assisted development using LLM coding tools; Develop AI-powered risk capabilities like investigation agents and automated decision support; Validate research-stage models for production readiness; Ensure models are explainable and traceable for governance; Design and deploy LLM-based agents for case triage and evidence retrieval; Build production-grade agent architectures with guardrails and human-in-the-loop controls; Develop evaluation frameworks for LLM agents measuring accuracy and operational impact
Seniority
Senior/Staff, hands-on IC with strategic impact
