Stripe - San Francisco, CA

posted about 1 month ago

Full-time - Mid Level
Remote - San Francisco, CA
Credit Intermediation and Related Activities

About the position

As a Machine Learning Engineer on the Payments ML Accelerator team at Stripe, you will play a pivotal role in developing capabilities that will enhance the use of machine learning (ML) techniques across Stripe's payment products. This position involves designing and building scalable platforms and services that are configurable, allowing for the deployment of advanced ML applications and feature engineering pipelines. Your work will directly contribute to producing significant business impact and raising the technical standards within the organization. You will also have the opportunity to influence the ML architecture at Stripe, ensuring that it meets the evolving needs of the business. The Payments ML Accelerator team is focused on creating cutting-edge deep learning models tailored to Stripe's payment data. This includes improving core product features such as fraud detection across various payment methods and optimizing payment acceptance rates. You will be involved in rapid ML exploration and fast experiment cycles, which are essential for the continuous improvement of Stripe's payment solutions. Your role will require collaboration with data scientists and the machine learning infrastructure team to leverage new services and build robust ML models that can be deployed in production environments. In this position, you will be expected to experiment with advanced ML solutions and ideate on product applications that can enhance the customer experience. You will also be responsible for establishing the foundation for increased adoption of deep neural networks (DNN) at Stripe, ensuring that the solutions you develop are not only effective but also scalable and maintainable.

Responsibilities

  • Build and deploy deep learning architectures and feature embeddings for Payment entities such as merchant, issuer, or customer
  • Develop DNN applications and establish the foundation to facilitate increased DNN adoption at Stripe
  • 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

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

Nice-to-haves

  • 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

Benefits

  • Equity
  • Company bonus or sales commissions/bonuses
  • 401(k) plan
  • Medical benefits
  • Dental benefits
  • Vision benefits
  • Wellness stipends
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service