Impact

As a Senior Machine Learning Engineer on our Fraud Detection & Risk Assessment Data Science team, you will design, build, and deploy cutting-edge ML systems that protect millions of users and multiple product lines from evolving fraud and risk threats. You’ll work with complex, high-volume data streams to develop models and infrastructure that identify anomalies, assess risk, and enable real-time decisioning across our ecosystem.

Collaborating closely with Product, Fraud Operations, Engineering and Data Science teams, you will translate business risk signals into robust machine learning pipelines—improving the accuracy, efficiency, and impact of our fraud detection systems. The ideal candidate brings deep technical expertise, strong engineering discipline, and a passion for applying ML to real-world risk problems. You thrive in a fast-paced environment and are excited to influence ML strategy and best practices across the organization.

Core Responsibilities:

Design, implement and optimize scalable production ready ML systems for fraud detection, risk scoring, and anomaly detection using structured and unstructured data.


Build and productionize end-to-end ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring.


Contribute to shape the ML roadmap enabling ML models as well as unfold Agentic AI capabilities for fraud detection and prevention.


Collaborate with data scientists to productionize statistical and ML models with a focus on low-latency, high-throughput, and real-time fraud detection.


Develop automated feedback loops for model retraining and continuous improvement as fraud patterns evolve.


Leverage experimentation frameworks (e.g., A/B testing, causal inference) to evaluate the impact and lift of fraud prevention models and systems.


Ensure model governance and compliance, including explainability, versioning, and audit readiness.


Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning, Gen AI and software engineering

What You’ll Need to Be Successful

• Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative discipline.
   

• 3+ years of experience in developing and deploying machine learning models in large-scale production environments, delivering measurable business impact.
   

• Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps.
   

• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
   

• Experience with data pipeline tools and frameworks (e.g., Airflow, Spark, Kafka, or similar).
   

• Strong understanding of feature engineering, model evaluation, monitoring, and drift management.
   

• Experience applying graph ML techniques to detect relational or network-based fraud patterns (e.g., NetworkX, PyTorch Geometric, etc) is highly desirable.
   

• Familiarity with GenAI/LLM ops, real-time personalization, or fraud detection is a plus
   

• Excellent problem-solving, communication, and cross-functional collaboration skills.

Skills & Education

This list includes key skills used in this job but is not inclusive of all skills needed for the role. Please see any required education below.

Data Science, Fraud Detection, Machine Learning (ML), Model Training

 

Bachelor's Degree or equivalent experience | Required

 

 

Work Arrangement

Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections. In-office expectations will vary by role and leader.  Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role.

About Shipt

Shipt is a retail tech company that connects people to reliable, high-quality delivery with a personal touch. Shipt connects customers to the things they want from the stores they love, retail businesses to more satisfied customers, and workers to new earning opportunities.

At Shipt, we aim to put our team first to boost a sense of belonging, spark opportu