Sr Engineer - Machine Learning

Job Title: Sr Engineer - Machine Learning

Company: Target

Location: Minneapolis, MN (On-site, Remote)

Salary: $95,000 - $171,000/yr

Type: Full-time

Benefits: Medical, Dental, Vision, Life, Retirement, PTO

Job Description: The Fraud Detection and Prevention Data Science team builds scalable, intelligent systems that safeguard Target's guests and digital channels from fraud and abuse. As a Senior Engineer, you will own the end‑to‑end lifecycle of machine learning solutions – from data exploration and feature engineering to model development, deployment, and continuous improvement through MLOps.

• Design, build, and scale ML models for fraud detection using supervised, unsupervised, and deep learning techniques.
• Perform exploratory data analysis (EDA) to identify anomalies, patterns, and emerging fraud behaviours.
• Develop and maintain end‑to‑end MLOps pipelines on Vertex AI and GCP – including training, evaluation, deployment, and monitoring.
• Partner with cross‑functional teams – Engineering, Data Engineering, Investigations, and Product – to operationalize fraud models and translate insights into prevention strategies.
• Research and prototype new detection techniques, including LLMs, anomaly detection, and behavioural modelling.
• Lead technical design reviews, mentor junior data scientists/engineers, and uphold best practices through code reviews and technical sessions.
• Maintain strong documentation and model governance, ensuring reliability, reproducibility, and scalability across the ML platform.

• Languages:
  
  Python, SQL
• Frameworks:
  Tensor Flow, PyTorch, Scikit‑learn
• Data & Platforms: GCP, Vertex AI, PySpark, Big Query, Hadoop, Hive
• MLOps & Automation: MLflow, Airflow, CI/CD frameworks
• Collaboration:
  
  Git Hub, JIRA, cross‑functional partnerships with Engineering, Data Platform, and Fraud Investigations

• Advanced degree (Master’s or PhD) in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 5‑8 years of hands‑on experience in data science, ML engineering, or applied machine learning with a proven track record of developing and deploying machine learning models.
• Proven ability to build, scale, and deploy production ML models from experimentation to production.
• Strong experience with MLOps and pipeline automation using cloud platforms (GCP / Vertex AI preferred).
• Proficiency in data cleaning, preprocessing, and augmentation techniques to ensure high‑quality training data.
• Experience in fraud detection, anomaly detection, or risk modelling preferred but not required.
• Excellent programming and collaboration skills; able to bridge the gap between data science, engineering, and business.

• Mid‑Senior level

• Full‑time

• Engineering and Information Technology

• Technology, Information and Internet