Machine Learning Engineer
Stripe · South San Francisco, CA
About this role
**Machine Learning Engineer** **Who we are** Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet. **What you’ll do** **Responsibilities** - 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** **Minimum requirements** - Bachelor’s degree (or foreign equivalent) in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus **two (2) years** of experience building and shipping ML systems in production. - **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 - Building and deploying ML models to solve business problems - **One (1) year** of experience in each of the following: - ML libraries and frameworks including PyTorch, TensorFlow, XGBoost, or Spark - Deep learning, including transformers, test-time compute, or reinforcement learning **Compensation & logistics** - **Salary:** $212,000 - $318,000/yr (base salary; commissions/bonuses may be additional if applicable) - **Work schedule:** 40 hrs/week - **Telecommuting:** 50% telecommuting permitted - **Positions:** Multiple positions available - **Additional benefits may include:** equity, company bonus or sales commissions/bonuses; 401(k); medical, dental, and vision benefits; wellness stipends **Other** - CA29 - #LI-DNI
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