Staff AI/ML Engineer
About The Position
Chime is hiring a Staff AI/ML Engineer for its Lending and Cashflow team within Data Science & Machine Learning. The team builds models, services, and platforms that support members’ financial lives. This role leads modeling for cash flow underwriting and member insights, using transaction and deposit data to make fair, accurate credit decisions, including for people who may be overlooked by traditional credit scores. The engineer will build and deploy machine learning systems using transactional and behavioral data to power credit decisions for products such as MyPay, Instant Loans, and SpotMe. This is an applied, end-to-end role: the engineer owns problems from initial framing through production deployment and measurable outcomes, and sets technical direction for cash-flow underwriting at Chime.
Requirements
- Track record of leading the design and production deployment of deep learning models, including multi-quarter initiatives spanning teams.
- Strong understanding of model architecture choices, training dynamics, and evaluation, with sound judgment in model design.
- Solid machine learning fundamentals, including classical modeling, evaluation design, and selecting appropriate metrics.
- Hands-on experience with the end-to-end ML lifecycle: training, experimentation, optimization, deployment, and monitoring.
- Experience working with messy real-world data, including label definition, data leakage, class imbalance, and train/serve skew.
- Strong proficiency in Python and SQL.
- Experience with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark.
- Working knowledge of modern ML infrastructure, including AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake.
- MLOps mindset for maintaining healthy production systems.
- Ability to work independently in ambiguous environments, influence technical direction beyond one’s team, and clearly explain model decisions to engineers, risk partners, and senior leaders.
Nice To Haves
- Experience with credit or underwriting models and familiarity with model governance, explainability, and fairness requirements, such as adverse action reason codes and fair lending testing.
- Experience building cash-flow or alternative-data underwriting features from bank transaction data, such as income and expense detection, balance trends, and transaction categorization.
- Experience deploying transformer models in production.
Responsibilities
- Lead the design, training, and deployment of deep learning and classical ML underwriting models using transaction and cash-flow data for approval decisions, line assignment, and loss forecasting.
- Own the model lifecycle from problem framing through training, evaluation, deployment, monitoring, and iteration, remaining accountable for models in production.
- Design and improve supporting systems, including feature pipelines, batch and real-time inference, monitoring, and retraining.
- Partner with Product, Engineering, Analytics, and Risk to translate ambiguous business problems into appropriate ML solutions.
- Connect model performance to member outcomes and business metrics, and use experimentation to demonstrate impact.
- Set the technical roadmap for Lending ML and raise team standards through design reviews, mentorship, and shared practices for model development, validation, and governance.
- Identify opportunities where AI/ML can create measurable member impact and recognize when a simpler approach is preferable.
Benefits
- Eligible full-time employees may receive bonuses, competitive equity, and benefits.
- Backup child, elder, and pet care.
- Subsidized commuter benefits for eligible employees.
- Comprehensive health, financial, and wellbeing benefits.
- Generous vacation policy and company-wide paid days off.
- One percent of time off to support local community organizations of the employee’s choice.
- Annual wellness stipend for eligible wellness-related expenses.
- Up to 22 weeks of paid parental leave for birthing parents and 12 weeks for non-birthing parents.
- Family planning reimbursement.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
