254K–380K USD / year
Staff Machine Learning Engineer, Radar
Machine learningRemote — United States
Published on 2026-10-07
These details were extracted automatically from the original listing. They may not be complete or fully up to date — it's worth checking the original job post.
About this role
As a Staff Machine Learning Engineer at Stripe, you will lead machine learning initiatives to enhance fraud detection in Stripe's payment network. You’ll work across the entire lifecycle of ML models, from research to deployment, impacting real-time systems used by thousands of businesses. Our team is rapidly evolving to counteract new fraud patterns and integrate cutting-edge AI solutions.
About the company
Stripe provides payment infrastructure and financial tools that help businesses accept payments, manage subscriptions, and move money globally. It serves startups through large enterprises with APIs for online and in-person commerce.
The team
Radar ML team
Stack
PyTorchTensorFlowXGBoostSpark
What you'll do
- Design, build, train, evaluate, and deploy ML models to detect fraud
- Create large-scale ML systems processing diverse data
- Experiment with ML models to improve data quality and accuracy
- Develop automated processes for model training and evaluation
- Integrate and ensure scalability of ML models in production
- Collaborate across teams to identify ML improvement opportunities
- Mentor engineers within the ML culture of the team
What we're looking for
- 10+ years of industry experience in ML systems
- Proficient with ML frameworks like PyTorch and TensorFlow
- Hands-on model design, training, and evaluation experience
- Experience deploying models at scale and data orchestration
- Strong collaboration skills and autonomy in work
Nice to have
- MS or PhD in ML/AI or related field
- Experience in fintech or financial data domains
- Background in NLP or text classification
- Familiarity with fraud detection or risk modeling
- Experience with deep learning architectures