Sr. AI engineer

Job Description

Sezzle is seeking a Sr. AI Engineer to oversee the design, development, and deployment of machine learning models that power and enhance their financial platform. The ideal candidate will drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment. This involves utilizing a combination of cloud services, open-source tools, and proprietary algorithms. The role requires blending machine learning development and operations (MLOps) to automate and optimize the full lifecycle of ML models.

Responsibilities:

• Design, Build, and Maintain Scalable ML Infrastructure
• Collaborate with Product Teams
• Develop Monitoring & Alerting Frameworks
• Support Cross-Departmental AI Utilization
• Provide Production Support
• Scale ML Architecture
• Mentor and Elevate Team Skills
• Stay Ahead of the Curve

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 one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• Proven track record of developing machine learning models from inception to business impact, demonstrating the ability to solve complex challenges with innovative solutions.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting the technical direction to achieve project goals efficiently.
• Experience working with relational databases, data warehouses, and using SQL to explore them.
• Strong familiarity with AWS cloud services, especially in deploying and managing machine learning solutions and scaling them in a cost-effective manner.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models.
• Comfortable with monitoring and observability tools tailored for machine learning models (e.g., Prometheus, Grafana, AWS CloudWatch) and experienced in developing recommender systems or enhancing user experiences through personalized recommendations.
• Solid foundation in data processing and pipeline frameworks (e.g., Apache Spark, Kafka) for handling real-time data streams.

Sezzle offers:

• A dynamic, fast-paced environment with abundant prospects for career advancement.