Please contact your Administrator to change your authorization settings.
Employee Applicant Privacy Notice
Who we are:
Shape a brighter financial future with us.
Together with our members, we're changing the way people think about and interact with personal finance.
We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.
The role
The Fraud and Risk Signals engineering team is responsible for building ML platform that can scale and power experiences that brings together all of SoFi's products and services in a cohesive way and helps our members get their money right every day. As a senior engineer on the Member team, you will be core to our vision of leveraging machine learning to power personalized experiences across SoFi.
In this role, you will help build a democratized machine learning platform that will enable every team at SoFi to train, deploy, and monitor models with confidence. You will build automation pipelines and instrument observability, while focusing on business metrics. The ideal candidate has experience in managing a production machine learning lifecycle. If you like iterating, learning and innovating on problems with company wide impact, we would love to have you in our team
What you'll do:
-
Architect and technically lead development of highly scalable machine learning systems that the entire company will use.
-
Build scalable tools and services for handling machine learning workflows
-
Collaborate with data scientists, engineers and product managers to deploy and maintain machine learning models
-
Identify and evaluate new patterns and technologies to improve performance, maintainability and elegance of our machine learning systems
-
Design software architecture and data flows for scalable machine learning development work
-
Communicate with peer engineers and product managers to build requirements and track progress
-
Attribute to a team culture that values effective collaboration, technical perfection, and innovation
What you'll need:
-
Bachelor's degree in a technical field
-
6+ years experience building end-to-end data systems as Platform Engineer, ML Engineer or Data Engineer.
-
Experience setting up an AI platform on Cloud (AWS, GCP or Azure)
-
Experience building systems with scalable data processing (Spark or SQL)
-
Fluent in Python, Java or C++
-
Familiarity with microservices
-
Familiarity with monitoring and alerting tools
-
Strong communication and technical leadership skills
-
Desire to mentor and help others improve their skills