Principal Machine Learning Engineer (Remote)

Sezzle - Minneapolis, MN

Full-time - Principal

Remote - Minneapolis, MN

Credit Intermediation and Related Activities

About the position

The Principal Machine Learning Engineer at Sezzle is a remote role focused on leading the design, development, and deployment of machine learning models that enhance the company's financial platform. This position involves creating scalable machine learning solutions for personalized recommendations, fraud detection, and credit risk assessment, while also integrating MLOps practices to optimize the lifecycle of ML models. The engineer will collaborate with a team of engineers and data scientists to deliver high-quality solutions that address challenges in the fintech space, ensuring the robustness and efficiency of AI-driven features as the company grows.

Responsibilities

• Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker.
• Collaborate with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing.
• Create and enhance monitoring and alerting systems for machine learning models to ensure high performance and reliability.
• Enable various departments to leverage AI/ML models for different use cases, including Generative AI solutions.
• Provide expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations.
• Design and scale machine learning architecture to support rapid user growth, ensuring robustness and efficiency.
• Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing.
• Stay updated with the latest advancements in machine learning technologies and AWS services.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience.
• At least 6+ years of experience in machine learning engineering, with demonstrated success in deploying scalable ML models in a production environment.
• Deep expertise in machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related fields.
• Proficiency with Python and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams and owning end-to-end projects.
• Experience working with relational databases and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment of ML models.
• Comfortable with monitoring tools for machine learning models and experienced in developing recommender systems.
• Solid foundation in data processing and pipeline frameworks for handling real-time data streams.

Nice-to-haves

• Experience with Prometheus, Grafana, and AWS CloudWatch for monitoring and observability.
• Experience in enhancing user experiences through personalized recommendations.

Benefits

• Flexible work environment with remote options.
• Opportunities for professional development and continuous learning.
• Inclusive company culture that values diversity and equal opportunity.