Staff ML Engineer, Open Banking Data & Risk

Stripe; New York (NY); Hybrid; USD 254,000 - 380,000; Full time

Benefits offered by this job

Equity

401(k)

Medical/Dental/Vision

Wellness stipends

Job summary

Stripe is seeking a Senior ML Engineer to design, train, and deploy production ML models that improve transaction categorization, risk scoring, and data enrichment across Financial Connections.

You will build large-scale ML systems operating on data from thousands of institutions, collaborate with product, data science, and engineering teams, and mentor engineers while advancing Stripe's ML engineering culture.

Qualifications

• 10+ years of industry experience building and shipping ML systems in production.
• MS or PhD in ML/AI or related field preferred; fintech experience a plus.
• Proficient with ML libraries and frameworks (PyTorch, TensorFlow, XGBoost) and Spark.

Responsibilities

• Design, train, deploy, and own production ML models for transaction categorization and risk scoring.
• Build large-scale ML systems operating on data from thousands of institutions.
• Experiment with ML models (PyTorch, TensorFlow, XGBoost) to improve data quality and accuracy.
• Develop pipelines to train/evaluate models offline and online.
• Integrate ML models into production systems ensuring scalability and reliability.
• Collaborate with product, data science, and engineering to improve merchant outcomes.
• Mentor engineers and contribute to a strong ML culture within the team.

Skills

ML engineering

PyTorch

TensorFlow

XGBoost

Spark

Data pipelines

Productionize models

Collaboration

Autonomy

Entrepreneurial mindset

Education

MS or PhD in ML/AI

Tools

PyTorch

TensorFlow

XGBoost

Spark

Job description

Stripe is seeking a Senior ML Engineer to design, train, and deploy production ML models that improve transaction categorization, risk scoring, and data enrichment across Financial Connections.

You will build large-scale ML systems operating on data from thousands of institutions, collaborate with product, data science, and engineering teams, and mentor engineers while advancing Stripe's ML engineering culture.