Growth ML Engineer - Personalization & Recommendations

Stripe; San Francisco (CA); Hybrid; USD 180,000 - 270,000; Full time

Benefits offered by this job

Equity

401(k) plan

Medical, dental, and vision benefits

Wellness stipends

Job summary

Stripe is seeking a machine learning engineer for the Growth Platform to build and operate production ML systems that improve product recommendations and next steps for businesses. You will own work from problem definition through deployment, monitoring, and iteration, partnering with data scientists, engineers, and product teams to drive measurable outcomes.

You will design and deploy models, improve bandits and policy learning, and develop data pipelines while ensuring reliability, latency,

Qualifications

• 3+ years of industry experience in machine learning engineering, software engineering, or applied data science.
• Hands-on experience building and shipping ML models in production.
• Strong programming skills in Python with maintainable, tested production code.
• Practical experience with ML frameworks (PyTorch, TensorFlow, XGBoost, scikit-learn).
• Able to design, train, and evaluate ML models and run experiments.
• Experience with data/feature pipelines, SQL, and distributed data processing (Spark/PySpark).
• Understanding of statistics, model evaluation, and experimentation to avoid data leakage.
• Experience deploying, monitoring, and debugging production ML systems.
• Ability to translate business problems into technical solutions and collaborate across teams.

Responsibilities

• Design, train, evaluate, deploy, and maintain models for recommendation, ranking, and personalized actions.
• Improve contextual bandit and policy-learning approaches and adapt to user context and feedback.
• Build agent-based recommendation capabilities using business context and evaluate usefulness.
• Develop data pipelines for training and inference; improve data freshness and feature quality.
• Create reusable tooling for model evaluation, retraining, and safe rollout.
• Own the quality and operation of ML components: code, monitoring, failure investigation, and cost optimization.
• Design and analyze online experiments; connect offline evaluation to product adoption and impact.
• Collaborate with product engineering and ML infrastructure to integrate models into delivery systems.
• Work with product, marketing, and sales to identify problems where ML adds value.

Skills

Python

PyTorch

TensorFlow

XGBoost

scikit-learn

SQL

Spark

PySpark

Statistics

Experimentation

Education

Bachelor's degree in a relevant field

Job description

Stripe is seeking a machine learning engineer for the Growth Platform to build and operate production ML systems that improve product recommendations and next steps for businesses. You will own work from problem definition through deployment, monitoring, and iteration, partnering with data scientists, engineers, and product teams to drive measurable outcomes.

You will design and deploy models, improve bandits and policy learning, and develop data pipelines while ensuring reliability, latency,