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# Machine Learning Engineer

- **Company:** Stripe, Inc.
- **Location:** South San Francisco, CA, United States (Remote available)
- **Salary:** $212,000.0 - $318,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, High-Level Architecture, Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Apache Spark, Deep Learning, Stripe, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Data Pipelines
- **Published:** August 21, 2026
- **Apply:** https://www.dice.com/job-detail/27bb6f86-66e4-4047-8264-f077888d730c

## About the Role

Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production.

Must have two (2) years of experience in each of the following:

 * ML algorithms and model architectures;
 * Designing, training and evaluating machine learning models;
 * Productionizing and deploying machine learning models at scale;
 * Orchestrating data pipelines and leveraging large-scale datasets; and
 * Building and deploying ML models to solve business problems.

Must have one (1) year of experience in each of the following:

 * ML libraries and frameworks including PyTorch, TensorFlow, XGBoost or Spark; and
 * Deep learning, including transformers, test-time compute, or reinforcement learning.

## Description

* Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints.
 * Design systems to speed up the time from idea to deployment of new models.
 * Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency.
 * 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 and strategy partners to propose, prioritize, and implement new product features.
 * Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions.

Who you are


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