Senior Machine Learning Engineer, Anomaly Detection

Potential Senior Machine Learning Engineer Role

Talent Network Notice: This page describes a potential future CargoGuard role. It does not mean CargoGuard is currently hiring for this position, and the responsibilities below describe potential future scope rather than current team structure or operations.

This future role would explore anomaly-detection methods that help surface unusual shipment activity for human review. The work could include location, identity, and shipment-event signals, with emphasis on testing, explainability, false-positive control, and production monitoring.

What You Will Do

• Design, train, and deploy anomaly detection models over streaming telematics, identity, and transaction data
• Build low-latency inference services appropriate for shipment-event analysis
• Evaluate graph-based models for relationships among carriers, brokers, drivers, devices, and shipment events
• Own the full ML lifecycle: feature engineering, experimentation, deployment, monitoring, and drift detection
• Partner with our fraud intelligence team to turn investigator insight into model features
• Balance precision, recall, explainability, and false-positive rates while documenting model limitations

What We Require

• 7+ years of experience building and shipping machine learning systems in production
• M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field
• Deep expertise in anomaly detection, time-series modeling, and unsupervised or semi-supervised learning
• Expert proficiency in Python and frameworks such as PyTorch, TensorFlow, XGBoost, or scikit-learn
• Proven experience deploying low-latency models on streaming data at scale
• Hands-on experience with MLOps tooling, feature stores, and model monitoring in cloud environments
• A track record of measurable impact in fraud, risk, security, or adversarial ML domains

What Sets You Apart

• Publications at NeurIPS, ICML, KDD, or similar venues
• Experience with graph neural networks or geospatial machine learning
• Background in payments fraud, cybersecurity, or telematics

About Our Talent Network

This page is part of the CargoGuard Talent Network. It describes a role that may become relevant as the company grows. Submitting your background does not create an employment relationship or guarantee that this position will open.

CargoGuard is an equal opportunity employer. We welcome applicants of every background and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic.

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