Description:

Sezzle is on a mission to financially empower the next generation by revolutionizing the shopping experience with innovative technology and interest-free installment plans.
The company is seeking a Principal Machine Learning Engineer who possesses both high IQ and high EQ to thrive in a dynamic, fast-paced environment.
This role involves overseeing the design, development, and deployment of machine learning models that enhance Sezzle's financial platform.
Responsibilities include creating scalable machine learning solutions for personalized recommendations, fraud detection, and credit risk assessment using cloud services and proprietary algorithms.
The engineer will lead the integration of machine learning development and operations (MLOps) to optimize the lifecycle of ML models.
Collaboration with engineers and data scientists is essential to build high-quality solutions addressing challenges in the shopping and fintech space.
The engineer will ensure AI-driven features are robust, efficient, and scalable as the company grows.

Requirements:

A Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience is required.
At least 6+ years of experience in machine learning engineering with a proven track record of deploying scalable ML models in production environments is necessary.
Deep expertise in machine learning, recommendation systems, pattern recognition, data mining, or artificial intelligence is preferred.
Proficiency in Python is required, and experience with Golang is a plus.
Demonstrated technical leadership in guiding teams and managing end-to-end projects is essential.
Experience with relational databases, data warehouses, and SQL is required.
Strong familiarity with AWS cloud services for deploying and managing machine learning solutions is necessary.
Knowledge of Kubernetes, Docker, and CI/CD pipelines for ML model management is preferred.
Experience with monitoring tools for machine learning models and developing recommender systems is required.
A solid foundation in data processing frameworks like Apache Spark or Kafka is necessary.

Working at Sezzle means being part of a team of brilliant engineers and passionate data enthusiasts who are committed to innovation.
The company culture emphasizes high standards, calculated risk-taking, and trust among team members.
Employees are encouraged to develop new ways of doing things and to continuously raise the bar for performance.
Sezzle offers a dynamic work environment that fosters collaboration and personal growth.