Machine Learning Engineer

Job Title: MLOps Engineer – AI/ML Fraud Detection (Wealth Management)

Location: US (Remote)

Overview:

We are seeking an MLOps Engineer to support real-time AI/ML fraud detection platforms within a Wealth Management and Financial Services environment. This role focuses on operationalizing machine learning models, building scalable SageMaker pipelines, and enabling high-quality feature engineering to ensure models move reliably from experimentation to secure, compliant production environments.

Key Responsibilities:

• MLOps & Model Operations: Build and maintain end-to-end pipelines for fraud detection, managing the full lifecycle including validation, deployment, and retraining.
• AWS SageMaker Engineering: Design and implement SageMaker Pipelines and Processing jobs to automate training and scalable data preparation workflows.
• Feature Engineering: Design and optimize feature pipelines to ensure high-quality, explainable data and consistency between training and real-time inference.
• Infrastructure & Traceability: Ensure reproducibility and versioning across all ML workflows while maintaining high availability for mission-critical fraud systems.
• Compliance & Governance: Apply FSI-regulated best practices, supporting audit requirements and security reviews typical of wealth management platforms.
• Strategic Collaboration: Partner with data scientists and platform teams to bridge the gap between model research and production-grade engineering.

Qualifications:

• Experience: 4+ years in MLOps, ML Engineering, or related roles with a proven track record of operationalizing models in production.
• Technical Skills: Expert proficiency in Python for ML and hands-on experience with AWS SageMaker (Pipelines, Processing, and deployment).
• Domain Expertise: Experience in Financial Services (FSI), specifically regarding AI/ML-driven fraud prevention or transaction-risk monitoring.
• Systems Design: Strong understanding of real-time data orchestration, model monitoring, and feature store management.

Education & Requirements:

• Bachelor’s degree in Computer Science, Data Science, or Engineering (or equivalent experience).
• Candidates must possess strong documentation skills and the ability to pass a comprehensive background check required for high-trust, regulated financial environments.