Remote Growth ML Engineer: Personalization & Recommendations

Stripe; United States; Remote; 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 to build and operate production ML systems that improve how we recommend products and actions to users. You will own from problem definition through deployment, working with data scientists, engineers, and product partners to drive measurable outcomes.

You will design, train, evaluate, and monitor models, optimize latency and cost, and translate business problems into scalable technical solutions while collaborating across Stripe teams.

Qualifications

• 3+ years of industry experience building and shipping ML models in production.
• Strong programming in Python and writing maintainable, tested production code.
• Experience designing, training, and evaluating ML models with PyTorch, TensorFlow, XGBoost, or scikit-learn.
• Experience building data or feature pipelines, proficiency in SQL, and familiarity with Spark / PySpark.
• A solid understanding of statistics, model evaluation, and experimentation with leakage awareness.
• Experience deploying, monitoring, debugging production ML systems with latency and cost considerations.
• Ability to translate open-ended business problems into technical approaches and collaborate cross-functionally.

Responsibilities

• Design, train, evaluate, deploy, and maintain models for recommendations and ranking.
• Improve contextual bandit and policy-learning approaches including exploration and reward design.
• Develop agent-based recommendation capabilities using business context for relevant products.
• Build data pipelines for training and inference with data freshness and feature quality.
• Create reusable tooling for model evaluation, retraining, and safe rollout.
• Own the quality, monitoring, and reliability of ML components and pipelines.

Skills

ML engineering experience

Python programming

Model evaluation

Production ML systems

Cross-functional collaboration

Tools

PyTorch

TensorFlow

XGBoost

scikit-learn

SQL

Spark / PySpark

Job description

Stripe is seeking a machine learning engineer to build and operate production ML systems that improve how we recommend products and actions to users. You will own from problem definition through deployment, working with data scientists, engineers, and product partners to drive measurable outcomes.

You will design, train, evaluate, and monitor models, optimize latency and cost, and translate business problems into scalable technical solutions while collaborating across Stripe teams.