Senior Machine Learning Engineer: ML Algorithms

Bachelor’s/Master’s in Computer Science, Engineering, or related
4+ years of machine learning experience with strong software engineering skills
Experience with Risk modeling for financial use cases is required
Proficiency in ML techniques (LLMs, deep learning, sequence, and tree-based models); credit/fraud risk and portfolio management knowledge is a plus
Advanced Python programming, SQL, and data manipulation skills
Experience with ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS Sagemaker, Databricks, GCP Vertex AI)
Excellent communication and collaboration abilities
A passion for continuous learning and personal growth in a dynamic work environment

Design, develop, A/B test, and deploy risk models while collaborating with data scientists to drive data-driven decisions
Enhance credit and fraud models by adding innovative features quarterly and leveraging the latest industry research
Monitor feature and model health, and communicate changes in model decisions
Explore and integrate advanced technologies, including deep learning and LLMs, in the risk domain
Lead by example to foster operational excellence and transformative change
Expand responsibilities as new product needs arise