We’re looking for Machine Learning Engineers to join our Data team. This is a unique opportunity to contribute at a company that’s on the verge of becoming the household name in financial products for the 50% of Americans who are not served by traditional financial institutions. 

Our core tech stack includes: Python, Kubernetes, GCP, Snowflake

You’ll thrive in this role if:

• You’re personally motivated to help improve the financial health of the 100 million working-class Americans who live paycheck-to-paycheck
• You have a good foundation in computer science (data structures, algorithms, design patterns) and apply solid fundamentals in your software engineering (test-driven development, code review, refactoring)
• You have developed and maintained production ML systems
• You are familiar with Python and cloud technology stacks like AWS or GCP
• You are more motivated by practical solutions than theoretical elegance
• You can communicate, collaborate, compromise, and be sensitive to the needs of your partners and teammates

We’re offering:

• A low-ego, respectful data team committed to solving practical problems together
• The chance to work at a company where machine learning is at the heart of the business and integral to both our day-to-day operation and our executive team’s strategic vision
• Excellent opportunities for career growth, with both management and technical tracks for advancement
• A team that values learning and approaches work with a “growth mindset”

You might be particularly excited about the role if you want:

• To architect machine learning platforms through a combination of established tools (e.g. Spark, Kubernetes, Airflow), development of in-house tools, and evaluation of emerging tools (like feature stores or BentoML)
• To work on fairness, accountability, and transparency in machine learning (FAccT ML) or explainable AI (XAI)

Education requirement:

• Bachelor of Science with 5 years of relevant experience or
• Master of Science with 3 years of relevant experience or
• Ph.D with 2 years of relevant experience