Hiring: Machine Learning Engineer - Fraud & Identity Security Company: Ziverge Location: United States Job Posted Time: 2026-09-16 14:15:05 Employment Type: Full-time / Remote Target Skills & Keywords : Agile, Java, Keras, Machine Learning, Pandas, PyTorch, Python, REST, SQL, Scala, Spark, TensorFlow, scikit-learn About the job Experience: •3 years of experience in large-scale machine learning, user behavior analysis, and fraud detection at leading internet companies; experience in the security domain is highly preferred. •Minimum 3 years of experience in large-scale machine learning, user behavior analysis, and fraud detection at leading internet companies; experience in the security domain is highly preferred. Required Skills: •This is a full-time, remote position. This role requires candidates based in the US or Canada, with strong working-hours overlap with the rest of the data team. •Understand business objectives and develop models that help identify and prevent credential stuffing, account takeover (ATO), and other fraud behaviors, along with metrics to track progress. •Explore and visualize data to understand the problem space, identify differences in data distribution, and select suitable ML algorithms. •Develop scalable and efficient methods for large-scale data analysis and model development. •Define data augmentation pipelines, train models and tune hyperparameters, deploy models to production, and monitor and evaluate ML model performance. •Investigate and resolve production issues, contributing to the ongoing reliability of deployed models. •Partner cross-functionally with developers, program managers, and product managers in an open, creative environment. •Analyze feature requirements, assess technical feasibility, and provide clear estimates and risk assessments. Qualifications: •Operational familiarity with Scala and data engineering — not required, but a plus. •Operational familiarity with Java/Scala more broadly. •Prior experience working in a consulting or professional services setting, delivering services to external clients. •The ideal candidate is a strong data scientist / machine learning engineer with a passion for applying ML to real-world identity security and fraud problems — someone who enjoys owning the full model lifecycle, from data exploration through production deployment and monitoring, in an open and collaborative environment. Compensation: •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!