Sr. AI Engineer - Marketing

About the role

This position is responsible for owning the end-to-end lifecycle of machine learning systems that directly power marketing initiatives and customer engagement for Sezzle. The hire will architect and deploy scalable models that translate complex data into actionable growth strategies. They will lead the design of intelligent solutions that optimize the customer journey across the marketplace. This role demands a rare blend of technical depth and business acumen to translate ambiguous problems into robust AI products. The individual will act as a key technical partner to marketing and product teams, ensuring AI initiatives align with overarching business goals. They will drive innovation by researching and implementing advanced methodologies that enhance personalization and conversion. Ultimately, this role shapes the AI foundation that powers Sezzle's marketing ecosystem.

Key facts

What you'll do

• Architect and deploy scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment to support marketing objectives.
• Collaborate with product and marketing teams to develop minimum viable products for AI-driven features, ensuring rapid iteration and market validation.
• Engineer and enhance monitoring and alerting frameworks for machine learning models to guarantee high performance, reliability, and minimal downtime of critical marketing systems.
• Enable cross-departmental collaboration by providing AI and machine learning expertise to the marketing team and other stakeholders for diverse strategic use cases.
• Offer production support and troubleshooting for machine learning models in live environments, participating in on-call rotations to resolve operational incidents.
• Design and scale machine learning architecture to accommodate rapid user growth, applying deep expertise in AWS and machine learning best practices.
• Conduct code reviews and mentor engineering team members to elevate overall technical capability and knowledge sharing.
• Maintain currency with the latest advancements in machine learning and AWS services to drive the adoption of cutting-edge competitive solutions.
• Partner with data scientists to build large-scale, high-quality solutions that solve complex challenges in the shopping and fintech environment.
• Oversee the full lifecycle of machine learning models from initial concept through deployment and continuous optimization.
• Ensure all AI-driven features are robust, efficient, and scalable to meet the demands of a growing global platform.
• Leverage cloud services, open-source tools, and proprietary algorithms to deliver innovative marketing technology solutions.

Requirements

• Hold a Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or possess equivalent practical experience.
• Demonstrate required experience working with Claude or equivalent large language model tools; candidates must be comfortable leveraging AI to enhance productivity, research, and communication.
• Possess a minimum of 6+ years of experience in machine learning engineering, with proven success in deploying scalable ML models in production environments.
• Exhibit strong problem-solving skills and the ability to manage multiple priorities in a fast-paced setting.
• Communicate effectively with both technical and non-technical stakeholders to align on goals and progress.
• Adhere to strict quality standards ensuring defects are resolved before progression.
• Work autonomously with a high degree of ownership and accountability for project outcomes.
• Thrive in a dynamic environment that values speed, innovation, and continuous improvement.

Nice to have

• Deep expertise in machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical fields.
• A proven track record of developing machine learning models from inception to measurable business impact.
• Proficiency with Python is required, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams and setting technical direction.
• Experience with relational databases, data warehouses, and SQL for data exploration.
• Strong familiarity with AWS cloud services for deploying and scaling machine learning solutions cost-effectively.
• Knowledge of Kubernetes, Docker, and CI/CD pipelines for efficient model management.
• Experience with monitoring and observability tools such as Prometheus, Grafana, and AWS CloudWatch.
• Background in developing recommender systems and enhancing user experiences through personalization.
• Solid foundation in data processing frameworks like Apache Spark and Kafka for real-time data streams.

Practical notes

#Li-remote #full-time