Staff Machine Learning Engineer, Radar

The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud.

In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers.

Responsibilities

• Design, build, train, evaluate, deploy, and own ML models in production that detect fraud across Stripe’s global payments network
• Design and build large-scale ML systems that operate on diverse and large scale data
• Experiment and iterate on ML models to achieve key business goals around data quality and accuracy
• Develop pipelines and automated processes to train and evaluate models in offline and online environments
• Integrate ML models into production systems and ensure their scalability and reliability
• Collaborate with product, data science, and engineering partners across Stripe to identify opportunities where ML can improve outcomes for merchants and consumers
• Engage with the latest ML/AI developments and take calculated risks in transforming innovative ideas into productionized solutions
• Mentor engineers and contribute to a strong ML engineering culture within the team

Requirements

• 10+ years of industry experience building and shipping ML systems in production
• Proficient with ML libraries and frameworks such as PyTorch, TensorFlow, XGBoost, as well as Spark
• Hands-on experience in designing, training, and evaluating machine learning models
• Hands-on experience in productionizing and deploying models at scale
• Hands-on experience in orchestrating data pipelines and efficiently leveraging large-scale datasets
• Strong collaboration skills and the ability to work across teams and contribute to peers' success
• Ability to thrive with a high level of autonomy and responsibility and an entrepreneurial mindset