Machine Learning Engineer, Payment Performance & Fraud
San Francisco, Seattle, Remote (North America)
Stripe
Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the team
The Payment Performance & Fraud organization optimizes each of the billions of dollars of transactions processed by Stripe annually on behalf of our users, maximizing successful transactions while minimizing payment costs and fraud. We own products like Radar end-to-end, developing machine learning models, building fast and scalable services and creating intuitive user experiences. We serve real-time predictions as part of Stripe’s payment infrastructure and architect controls that leverage ML to optimally manage users’ business.
What you’ll do
As a backend engineer, you will design and build platforms and services that are configurable and scalable around the globe. You will partner with many functions at Stripe, with the opportunity to both work on infrastructure/platform systems, as well as produce direct user-facing business impact.
Responsibilities
- Design machine learning systems and pipelines for training and running machine learning models that improve the efficiency of transactions on Stripe. This could involve:
- Building prediction models for new aspects of transaction outcomes, like whether we expect to win a dispute given auto-submitted evidence.
- Improving the accuracy of our prediction models for transaction outcomes, like whether a payment will be accepted or declined by the card network, or disputed as fraudulent by a cardholder.
- Understanding our users’ business needs in order to evaluate model performance and improve the value model we use to evaluate transaction outcomes.
- Developing and evaluating new model architectures which improve the accuracy of our prediction models.
- Incorporate new features and sources of data.
- Writing simulation code on our distributed clusters to help us understand what would happen across different segments if we changed how we action our models.
- Integrating new models and behaviors into Stripe’s core payment flow.
- Collaborating with our machine learning infrastructure team to build support for new model types into our scoring infrastructure.
- Mentor engineers earlier in their technical careers to help them grow
Who you are
We’re looking for people with a strong background and passion in building successful backend systems, services and APIs that deliver impactful product values to our customers. You are comfortable in dealing with changes. You love to take initiatives, and bias towards action.
We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
- At least 5 years years industry experience doing software development on a data or machine learning team
- An advanced degree in a quantitative field (e.g. stats, physics, computer science) and some experience in software engineering in a production environment.
- Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis.
- The ability to thrive in a collaborative environment involving different stakeholders and subject matter experts.
- Pride in working on projects to successful completion involving a wide variety of technologies and systems.
- Comfort working directly with your users.
- Empathy with users and a strong customer focus
- Enjoyment in working with a diverse group of people with different expertise
Preferred qualifications
-
- Experience with or interest in ML, which powers many of the products we own
- Experience in payments and/or fraud
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Architecture Computer Science Engineering Machine Learning ML infrastructure ML models Physics Pipelines Radar
Perks/benefits: Career development
More jobs like this
Explore more AI, ML, Data Science career opportunities
Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
- Open Data Science Manager jobs
- Open MLOps Engineer jobs
- Open AI Engineer jobs
- Open Senior Business Intelligence Analyst jobs
- Open Sr Data Engineer jobs
- Open Data Engineer II jobs
- Open Data Manager jobs
- Open Principal Data Engineer jobs
- Open Data Analytics Engineer jobs
- Open Power BI Developer jobs
- Open Junior Data Scientist jobs
- Open Product Data Analyst jobs
- Open Data Scientist II jobs
- Open Senior Data Architect jobs
- Open Business Intelligence Developer jobs
- Open Sr. Data Scientist jobs
- Open Manager, Data Engineering jobs
- Open Big Data Engineer jobs
- Open Data Analyst Intern jobs
- Open Business Data Analyst jobs
- Open Data Quality Analyst jobs
- Open Data Product Manager jobs
- Open Junior Data Engineer jobs
- Open ETL Developer jobs
- Open Principal Data Scientist jobs
- Open Data quality-related jobs
- Open Business Intelligence-related jobs
- Open GCP-related jobs
- Open ML models-related jobs
- Open Data management-related jobs
- Open Privacy-related jobs
- Open Java-related jobs
- Open Finance-related jobs
- Open Data visualization-related jobs
- Open APIs-related jobs
- Open Deep Learning-related jobs
- Open PyTorch-related jobs
- Open Consulting-related jobs
- Open TensorFlow-related jobs
- Open Snowflake-related jobs
- Open PhD-related jobs
- Open NLP-related jobs
- Open CI/CD-related jobs
- Open Kubernetes-related jobs
- Open Airflow-related jobs
- Open Data governance-related jobs
- Open Databricks-related jobs
- Open Hadoop-related jobs
- Open LLMs-related jobs
- Open Data warehouse-related jobs