Senior AI Engineer – Marketing

🕒 May 13

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Sezzle

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2016

💳 Fintech

👥 B2C

🛍️ eCommerce

Fintech • B2C • eCommerce

Sezzle is a financial technology company that offers a "buy now, pay later" service, allowing consumers to purchase products and pay for them in four interest-free installments over six weeks. The Sezzle app provides users with a flexible financing alternative to traditional credit cards, enabling instant approval decisions without impacting credit scores. Sezzle partners with various top brands, including Amazon, Walmart, and Target, to offer in-app and in-store payment options. The company's mission is to empower consumers financially by providing more financial freedom and control. It is available as a mobile app, with millions of downloads and high user ratings, and works towards accessibility and inclusion on its platform.

📋 Description

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment. • Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively. • Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime. • Support Marketing Team’s AI Utilization with an eye on Cross-Departmental impact: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases. • Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution. • Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency. • Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration. • Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

🎯 Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience. • Demonstrated experience working with Claude or equivalent large language model tools is required; candidates must be comfortable leveraging AI to enhance productivity, research, and communication. • 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.

🏖️ Benefits

• Not specified