Senior AI Engineer

🕒 Setembro 27, 2025

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Sezzle

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2016

💳 Fintech

👥 B2C

🛍️ Comércio Eletrônico

Fintech • B2C • eCommerce

Sezzle é uma empresa de tecnologia financeira que oferece um serviço de compre agora, pague depois, permitindo que os consumidores comprem produtos e paguem em quatro parcelas sem juros ao longo de seis semanas. O app da Sezzle oferece aos usuários uma alternativa de financiamento flexível aos cartões de crédito tradicionais, possibilitando decisões de aprovação instantâneas sem impactar o score de crédito. A Sezzle faz parceria com diversas marcas líderes, incluindo Amazon, Walmart e Target, para oferecer opções de pagamento no app e na loja. A missão da empresa é empoderar financeiramente os consumidores, proporcionando mais liberdade e controle financeiros. Disponível como aplicativo móvel, com milhões de downloads e altas avaliações dos usuários, a Sezzle trabalha pela acessibilidade e inclusão em sua plataforma.

Descrição

• Lead the design, development, and maintenance of scalable ML infrastructure on AWS, utilizing services like AWS SageMaker for model training and deployment. • Collaborate with product teams to develop MVPs for AI-driven features and enable rapid iteration and market testing. • Create and enhance monitoring and alerting frameworks to ensure high performance, reliability, and minimal downtime of ML models. • Enable cross-departmental use of AI/ML models, including Generative AI solutions, for various organizational use cases. • Provide production support: debug and resolve issues related to ML models in production and participate in on-call rotations. • Design and scale ML architecture to support rapid user growth, optimizing for robustness and cost-effectiveness. • Mentor team members, conduct code reviews, and elevate overall team capabilities through knowledge sharing and collaboration. • Stay updated with the latest advancements in machine learning technologies and AWS services and drive adoption of cutting-edge solutions.

🎯 Requisitos

• 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. • Proficiency with Python (required); experience with Golang is a plus. • Demonstrated technical leadership in guiding teams, owning end-to-end projects, and setting technical direction. • Experience working with relational databases, data warehouses, and using SQL to explore them. • Strong familiarity with AWS cloud services, especially AWS SageMaker, for deploying and scaling ML solutions. • Knowledge of Kubernetes, Docker, and CI/CD pipelines for efficient deployment and management of ML models. • Comfortable with monitoring and observability tools tailored for ML models (e.g., Prometheus, Grafana, AWS CloudWatch). • Experience 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. • Willingness to provide production support and participate in on-call rotations for operational troubleshooting and incident resolution.