Plaid
Senior Machine Learning Engineer - Fraud
$229K–$315K
San Francisco HQ +2 · Hybrid · Senior · Full-time · Posted Sep 12, 2026
- Location
- San Francisco HQ
Seattle Office
New York City Office - Experience
- 7+ years of professional experience in machine learning, applied science, or software engineering for ML.
About the job
Develop and deploy machine learning models that detect fraud across Plaid’s network, leading projects from signal discovery and experimentation through production monitoring and improvement.
What you'll do
- Investigate fraud patterns and model errors; develop features, datasets, and experiments to improve detection.
- Build, evaluate, and deploy models and reproducible training pipelines, measuring real-world performance.
- Lead ML projects through release with Data Science, Product, Engineering, and ML Infrastructure partners.
What they ask for
- 7+ years of professional experience in machine learning, applied science, or software engineering for ML, including hands-on model development and deployment.
- Experience designing, training, tuning, deploying, and evaluating models; strong ML and statistical fundamentals.
- Experience constructing training datasets and addressing label quality, data leakage, class imbalance, and generalization.
- Strong Python skills, SQL proficiency, and hands-on experience with ML frameworks such as PyTorch, scikit-learn, XGBoost, or equivalents.
Nice to have
- Fraud or risk modeling experience; familiarity with fraud patterns, delayed feedback, and balancing detection with legitimate-user friction.
- Experience with graph-based predictive signals or newer approaches such as learned representations, transformers, or foundation models.
Pay
$228,960 – $315,360 (USD; base salary)
Tools
Python, SQL, PyTorch, scikit-learn, XGBoost, gradient-boosted trees, neural networks
AI focus
Explore how LLMs and Generative AI can improve fraud detection, prevention, and investigation.
Model-written summary · the original posting is authoritative