Senior Machine Learning Engineer (Modeling)
- San Francisco, CA, USA
- Employees can work remotely
- Alternate Location: Seattle, United States
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic app, bringing a better way to send, spend, invest, borrow and save to our millions of monthly active users. With a mission to redefine the world's relationship with money by making it more relatable, available and accessible, at Cash App you'll have the opportunity to make a real-world impact with your career.
Today, Cash App has thousands of employees around the world with a culture geared toward creativity, collaboration and impact. We’ve been a distributed team since day one, and continue to value working across time zones and continents both remotely and in our Cash App offices.
Our offices are great, but many of our roles can be done remotely from the countries where Block operates. We tailor our experience to champion our employees’ creativity and productivity wherever they are.
Machine Learning is an integral part of how we design products, operate, and pursue Cash App’s mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use artificial intelligence to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day.
This role is part of our Cash App's ML team and will be deeply embedded within one of our product teams - here are the workstreams we're currently hiring for:
Search & Discovery
Cash App enables millions of people and businesses to pay and get paid with ease. On our team, we build delightful experiences that help our customers find and discover people and things quickly and with trust - we aim to grow and strengthen the connections between people and businesses across the globe. Through your work, you will empower Cash App to personalize customers’ search and discovery experiences using AI/ML, to better understand our customers’ payment journeys, and help identify and execute on new opportunities for product improvement. You will employ a variety of modeling techniques on our comprehensive customer data and scale your solution to production by partnering closely with design, product, analytics, and engineering teams.
You'll build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal (including 3rd party data) to engineer new features for risk models, verify customer documents using OCR, and use biometric and device signals to detect malicious logins and account takeovers.
Customer Support Automation
Working closely with our Customer Support team, you will use our vast amounts of data to make experiences seamless for our customers and help us achieve world-class service as Cash App continues its rapid growth. You will build models that anticipate customer issues and deliver proactive in-app suggestions, use NLP to contextualize inquiries and respond instantly with relevant content, develop prioritization algorithms that improve efficiency, and apply the latest research to automate conversations with customers.
Technologies we use (and teach):
- Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
- MySQL, Snowflake, GCP/AWS and Tableau
- 3+ years experience with applied Machine Learning or Deep Learning
- A graduate degree in Computer Science, AI, ML, Applied Math, Stats, Physics, or a related technical field
- Worked with Product, Design, and Engineering to prioritize, scope, design, and deploy ML models
- A track record of providing mentorship and technical leadership
- An appreciation for the connection between the software you build and the experience it delivers to customers
We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page.
Additionally, we consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.