Growth Platform ML Engineer - Remote Options

Stripe; Chicago (IL); Hybrid; USD 180,000 - 270,000; Full time

Benefits offered by this job

Equity

Bonus

401(k)

Medical/Dental/Vision

Wellness stipend

Job summary

Stripe is hiring a machine learning engineer to build and operate production ML systems that optimize how Stripe recommends products and actions to businesses. You will lead from problem definition through deployment, working with data scientists, engineers, and product partners to deliver measurable outcomes.

The role emphasizes designing, training, and evaluating models with frameworks like PyTorch or TensorFlow, building feature pipelines, and monitoring performance in production.

Qualifications

• 3+ years of industry experience in machine learning engineering, software engineering, or applied data science.
• Strong programming skills in Python.
• Practical experience designing, training, and evaluating ML models using PyTorch, TensorFlow, XGBoost, or scikit-learn.
• Experience building data or feature pipelines, proficiency in SQL, and familiarity with distributed data processing tools such as Spark or PySpark.
• A strong understanding of statistics, model evaluation, and experimentation, including data leakage awareness.
• Experience deploying, monitoring, and debugging production ML systems, balancing quality, latency, and cost.
• Ability to translate open-ended business problems into a technical approach and collaborate with teams.

Responsibilities

• Design, train, evaluate, deploy, and maintain models for recommendation, ranking, and personalized action selection.
• Improve contextual bandit and policy-learning approaches, including exploration and reward design.
• Build agent-based recommendation capabilities using business context.
• Develop reliable data and feature pipelines for training and inference.
• Create reusable tooling for model evaluation, retraining, and safe rollout.
• Own the quality and operation of ML components: monitor, investigate failures, and optimize latency and cost.
• Design and analyze online experiments with data science partners and connect offline evaluation to product impact.
• Collaborate with product engineering and ML infrastructure teams to integrate models into delivery systems.
• Identify problems where modeling adds value and translate into actionable solutions.

Skills

Python

Production ML

PyTorch

TensorFlow

scikit-learn

Spark

SQL

Statistics

Experimentation

Deployment

Tools

PyTorch

TensorFlow

scikit-learn

Spark

SQL

Job description

Stripe is hiring a machine learning engineer to build and operate production ML systems that optimize how Stripe recommends products and actions to businesses. You will lead from problem definition through deployment, working with data scientists, engineers, and product partners to deliver measurable outcomes.

The role emphasizes designing, training, and evaluating models with frameworks like PyTorch or TensorFlow, building feature pipelines, and monitoring performance in production.