Machine Learning Engineer, Payments ML Accelerator

Key Skills

Deep Learning, Design, Machine learning techniques, Python Programming, Scala Programming, SPARK Programming, Statistics

Job Description

About the team

The newly formed Payments ML Accelerator team is developing capabilities that will unlock the proliferation of ML based techniques across Stripe’s payment products. We are developing cutting edge deep learning models tailored to Stripe’s payment data, and infrastructure to enable rapid ML exploration and very fast experiment cycles. We are exploring novel applications powered by ML as well as improving core product features such as detecting fraudulent transactions across all payment methods or optimizing payment acceptance rate.

What you'll do

As a machine learning engineer, you will design and build platforms and services that are configurable and scalable. You will have the opportunity to build and deploy advanced ML applications and generalizable feature engineering pipelines, with the aim to produce business impact and raise the bar for technical excellence. You will also have the opportunity to contribute to and influence ML architecture at Stripe. 

Responsibilities

• Build shared Payments ML infrastructure such as a centralized Payments Feature Store
• Build and deploy deep learning architectures and feature embeddings for Payment entities such as merchant, issuer, or customer
• Design and architect generalizable ML workflows for rapid expansion of existing ML solutions
• Experiment with advanced ML solutions in the industry and ideate on product applications
• Collaborate with our machine learning infrastructure team to leverage new infra services for business solutions
• Collaborate with data scientists to build ML models

Who you are

We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action

Minimum requirements

• At least 5 years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production
• Advanced degree in a quantitative field (e.g. computer science, statistics, physics, …)
• Proficient in Python, Scala, Spark

Preferred qualifications

• Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis.
• Experience evaluating niche and upcoming ML solutions

Pay and benefits

The annual US base salary range for this role is $187,000 - $253,000. For sales roles, the range provided is the role’s On Target Earnings (OTE) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.