Deep Learning Engineer (Dessa), Cash App
- Toronto, ON, Canada
- Employees can work remotely
- Alternate Location: San Francisco, United States
- Current Square Employee?: Apply via go/jobs with your Square email.
Cash App is the fastest growing financial brand in the world. 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 with over 30 million monthly active users. We are bringing a better way to send, spend, invest, and save to anyone who has ever sought an alternative to the traditional banking system.
Loved by customers and pop culture, we’ve consistently held the top spot for finance in the App Store for many years, seeing more engagement with millions of followers across social media in a day than most brands see in a year. We are building an ecosystem to redefine the world’s relationship with money by making it universally accessible. We want to hire the best talent regardless of location.
Our employment model is distributed, offering the opportunity to collaborate with teams across the world in San Francisco, New York, St. Louis, Portland, Toronto, Kitchener-Waterloo, Sydney, and Melbourne.
Dessa researches and develops applications for emerging machine learning technologies at Cash App. We're a small team of engineers focussed on building machine learning longshots, balancing a passion for advancing what's possible with a commitment to positive real-world impact. In collaboration with teams at Cash App, we're developing machine learning-powered products to promote economic empowerment.
We're looking for a Deep Learning Engineer to join Dessa to help us achieve our mission. As part of our team, you'll have a significant amount of creative freedom and time to work on projects aimed at advancing machine learning's real-world potential. Dessa is a culture dedicated to creativity, inclusion, and making a positive impact. If this sounds like the kind of environment you'd thrive in, we would love to talk.
- Manage the full lifecycle of ML development - problem framing, data wrangling, model development and production
- Contribute to the development of ML applications that solve real business problems at Cash App
- Develop experimental projects focussed on developing novel ML technologies, part of an initiative we call 'Bananas'
- Oversee ML model performance - maintaining accuracy and managing tradeoffs on user/product performance
- Deepen your ML knowledge by reading new research, presenting at workshops and guiding co-ops
- 3+ years of machine learning experience, especially developing production-ready deep learning systems
- An understanding of general data manipulation and experience with large data sets (1TB+)
- Strategies for creating order out of chaos—we often encounter net-new problems and work on solutions without a clear-cut strategy
- Collaborated with diverse teams across different disciplines
Some technologies we teach and use:
- Tensorflow or PyTorch
- SQL, Spark, Snowflake and BigQuery
Cash App treats all employees and job applicants equally. Every decision is based on merit, qualifications, and talent. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We will consider for employment qualified applicants with criminal histories in a manner consistent with each office’s corresponding local guidelines.