Staff Machine Learning Engineer

Who you are

• 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
• MS or PhD degree in ML/AI or a related field (e.g., math, physics, statistics, computer science)
• Experience in fintech, open banking, or financial data domains
• Experience with NLP, LLMs, or text classification at scale
• Experience in adversarial or noisy-data domains such as fraud detection, risk modeling, or data quality
• Proven track record of building and deploying ML systems that have effectively solved ambiguous business problems
• Experience with deep learning architectures, including transformers

What the job involves

• 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
• You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch
• 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

Benefits

• Gym membership
• Food provided in the office
• Unlimited paid time off policy
• Work from home opportunities
• Comprehensive mental, physical and medical health plans
• Fertility benefits and parental leave