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# machine learning engineers

- **Company:** Stripe, Inc.
- **Location:** New York, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Online Banking, Fraud Prevention and Detection, Machine Learning, Tensorflow, Pytorch, Large Language Models, Apache Spark, Deep Learning, Build Management, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Document Classification, Data Pipelines
- **Published:** August 28, 2026
- **Apply:** https://www.dice.com/job-detail/9b9c0fe1-a908-40be-afdc-a34e9e10e13d

## About the Role

* 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

## Description

* Design, build, train, evaluate, deploy, and own ML models in production that improve transaction categorization, risk scoring, and data enrichment across Financial Connections
 * Design and build large-scale ML systems that operate on diverse financial data from thousands of institutions
 * Experiment and iterate on ML models (using tools such as PyTorch, TensorFlow, XGBoost) 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


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