Machine Learning Engineer Machine Learning

Position: Staff Machine Learning Engineer United States of America Machine Learning[...]
## Staff Machine Learning Engineer San Jose, California, United States of America
** The Company
** Pay Pal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, Pay Pal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. Pay Pal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a Pay Pal or Venmo account balance, Pay Pal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards.  

Our Pay Pal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk.

We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day.  We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.
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* Job Summary:

** As a Machine Learning Engineer on Venmo’s Data Science team, you’ll tackle high-impact challenges that shape how millions of people move and manage money with friends, family, and businesses. Our work spans personalization, retention, trust, discovery, and growth — from predicting churn before it happens to powering Venmo’s search and recommendations, to building smarter fraud and risk models. You’ll leverage Venmo’s unique social graph and financial ecosystem to design ML solutions that drive engagement, safety, and meaningful product experiences.
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* Job Description:

** You’ll be a senior technical leader and thought partner across Venmo—building production-scale ML solutions that serve millions of users and strengthen the core of our product experience, with a growing focus on agentic AI and its role in shaping the future of commerce. From developing models that personalize interactions to optimizing search and discovery, your work will directly shape the future of how people move money and connect through Venmo.

You’ll collaborate closely with engineering, product, and operations teams—pushing the boundaries of what’s possible with ML and helping evolve the data science culture  Roles and

Responsibilities include:

- Design, build, and deploy production-grade machine learning models that power personalization, search, ranking, discovery, and other core product experiences.  - Use machine learning to drive monetization and deliver user value—supporting initiatives such as pricing strategy, feature optimization, and behavioral targeting.  - Partner with product managers, engineers, and designers to identify high-impact opportunities, frame problems as ML tasks, and define measurable success.  

- Lead the full lifecycle of model development—from data exploration and feature engineering to validation, deployment, and…