Contract W2/ 1099 | Senior Databricks ML Engineer Fraud Detection / Anomaly Detection | Remote

Senior Databricks ML Engineer Fraud Detection / Anomaly Detection

Job Type: Contract W2/ 1099
Location: Remote EST/CST Time Zone
Duration: Long-Term Contract

Job Summary

We are seeking a Senior Databricks ML Engineer with strong hands-on experience building and deploying machine learning solutions for fraud detection and anomaly detection, preferably within the payments, banking, financial services, or FinTech industry.

The ideal candidate will have strong practical experience with Databricks Machine Learning, feature engineering, Feature Store, MLflow, XGBoost, Isolation Forest, Structured Streaming, and Model Serving.

Key Responsibilities

• Design, develop, and productionize machine learning solutions for fraud and anomaly detection use cases.
• Build scalable ML pipelines using Databricks and Apache Spark.
• Develop and manage features using feature engineering and Feature Store capabilities.
• Use MLflow for experiment tracking, model management, versioning, and lifecycle management.
• Develop supervised and unsupervised ML models using techniques such as XGBoost and Isolation Forest.
• Build and optimize Structured Streaming pipelines for real-time transaction and event processing.
• Deploy machine learning models using Databricks Model Serving.
• Develop scalable and reliable ML workflows for production environments.
• Collaborate with data engineers, data scientists, product teams, and business stakeholders to translate fraud detection requirements into technical solutions.
• Monitor and improve model performance, reliability, and scalability.
• Follow MLOps best practices for model development, deployment, and lifecycle management.

Required Skills

• 10+ years of experience in Machine Learning, Data Science, ML Engineering, or related areas.
• Strong hands-on experience with Databricks.
• Experience developing fraud detection or anomaly detection solutions.
• Strong experience with feature engineering and Feature Store capabilities.
• Hands-on experience with MLflow.
• Strong experience with XGBoost.
• Experience with Isolation Forest or other anomaly detection techniques.
• Strong experience with Spark Structured Streaming.
• Experience deploying production ML models using Databricks Model Serving.
• Strong Python and PySpark experience.
• Experience working with large-scale structured data and real-time transaction/event data.

Preferred Industry Experience

• Payments
• Banking
• Financial Services
• FinTech
• Credit Cards
• Transaction Processing
• E-commerce Payments

Preferred Additional Skills

• Kafka
• Delta Lake
• SQL
• Cloud platforms such as AWS, Azure, or Google Cloud Platform
• MLOps
• CI/CD
• Model monitoring and performance optimization