Remote Principal Machine Learning Engineer (LATAM, Remote)

Description:

• Sezzle is a leading financial technology company focused on empowering consumers with flexible payment options and innovative shopping experiences.
• The Principal Machine Learning Engineer will join the core AI/ML team to oversee the design, development, and deployment of machine learning models for Sezzle's financial platform.
• This role involves creating scalable machine learning solutions for personalized recommendations, fraud detection, and credit risk assessment using cloud services, open-source tools, and proprietary algorithms.
• The engineer will blend machine learning development and operations (MLOps) to automate and optimize the full lifecycle of ML models.
• Responsibilities include designing scalable ML infrastructure on AWS, collaborating with product teams, developing monitoring frameworks, supporting cross-departmental AI utilization, providing production support, scaling ML architecture, mentoring team members, and staying updated with advancements in machine learning technologies.

Requirements:

• A Bachelor's degree in Computer Science, Computer Engineering, Machine Learning, Statistics, Physics, or a relevant technical field, or equivalent practical experience is required.
• At least 6+ years of experience in machine learning engineering with a proven track record of deploying scalable ML models in a production environment is necessary.
• Deep expertise in machine learning, recommendation systems, pattern recognition, data mining, or related fields is preferred.
• Proficiency in Python is required, with experience in Golang considered a plus.
• Demonstrated technical leadership and experience in guiding teams and managing end-to-end projects is essential.
• Familiarity with relational databases, data warehouses, and SQL is required.
• Strong knowledge of AWS cloud services for deploying and managing machine learning solutions is necessary.
• Experience with Kubernetes, Docker, and CI/CD pipelines for ML model management is preferred.
• Comfort with monitoring tools for machine learning models and experience in developing recommender systems is required.
• A solid foundation in data processing and pipeline frameworks for handling real-time data streams is necessary.

Benefits:

• Sezzle offers a dynamic work environment that values high standards and encourages innovation.
• Employees are surrounded by talented individuals, fostering a culture of excellence and collaboration.
• The company is committed to diversity and inclusion, creating an enriching employment experience for all employees.
• Sezzle promotes a culture of calculated risk-taking and values speed in decision-making.
• The organization supports personal and professional growth through mentorship and knowledge sharing.