• Lead the design and development of scalable machine learning infrastructure on AWS. • Work closely with product teams to develop MVPs for AI-driven features. • Create and enhance monitoring and alerting systems for machine learning models. • Enable various departments within the organization to leverage AI/ML models. • Offer expertise in debugging and resolving issues related to machine learning models in production. • Design and scale machine learning architecture to support rapid user growth. • Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing.

• Oversee the design, development, and deployment of machine learning models that enhance our financial platform. • Drive the creation of scalable machine learning solutions for personalized recommendations in the Sezzle marketplace, fraud detection, and credit risk assessment. • Collaborate with a team of engineers and data scientists to build large-scale, high-quality solutions that address challenges in the shopping and fintech space. • Design and build scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker. • Work closely 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. • Enable various departments to leverage AI/ML models, including Generative AI solutions, for different use cases. • Provide expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations. • Mentor team members through knowledge sharing and collaboration.

• Contribute to the design and development of AI-powered platforms and systems, working alongside senior engineers on complex initiatives. • Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration. • Build AI-driven features, intelligent automation, and agentic systems that enhance customer experiences and improve team productivity. • Embed AI capabilities into existing team workflows, products, and processes, ensuring solutions integrate naturally. • Build full-stack components spanning backend services, APIs, data layers, and frontend interfaces. • Collaborate with engineers, teams, and stakeholders across the company to understand requirements and deliver impactful solutions.

• Contribute to the design and development of AI-powered platforms and systems, working alongside senior engineers on complex initiatives. • Own end-to-end delivery of complex projects, from problem discovery and system design through production rollout and iteration. • Build AI-driven features, intelligent automation, and agentic systems that enhance customer experiences and improve team productivity. • Embed AI capabilities into existing team workflows, products, and processes, ensuring solutions integrate naturally. • Integrate AI capabilities into customer-facing products, internal tools, and operational workflows. • Build full-stack components spanning backend services, APIs, data layers, and frontend interfaces. • Translate business and operational problems into maintainable, AI-enabled technical solutions with guidance from senior team members. • Apply systems thinking to ensure reliability, performance, and security across platforms. • Collaborate with engineers, teams, and stakeholders across the company to understand requirements and deliver impactful solutions. • Participate in production support and incident response for team-owned systems, learning operational best practices. • Engage in code reviews and knowledge sharing to continuously improve skills and contribute to team growth.