Senior Machine Learning Engineer (Zelus Analytics) - Global Remote

Teamworks, the Operating System for Sports™, powers more than 6,500 sports organizations worldwide, including collegiate athletic departments and teams across all major professional leagues. With 300 exceptional employees located in ten different countries, Teamworks’ software solutions drive the operations of the most recognizable sports properties in the world.

Zelus Analytics, now part of Teamworks, is a premier sports intelligence platform that partners with teams across the NBA, MLB, NFL, IPL, NHL, and European football leagues. As a key component of Teamworks, Zelus continues to deliver cutting-edge analytics, empowering these organizations with advanced data insights to enhance performance, strategy, and decision-making. The platform integrates comprehensive sports data, enabling teams to gain a competitive edge through rich analysis and innovative solutions tailored to their specific needs.

We are seeking a passionate and highly skilled Senior Machine Learning Engineer to join our Analytics team. This role is crucial in advancing our market-leading sports intelligence platform, helping professional teams across various sports leverage cutting-edge machine learning models to compete at the highest levels. Your work will directly impact our exclusive network of partners as they strive to win championships.

This is a fantastic opportunity to be at the forefront of sports analytics technology and to contribute to the ongoing success and rapid expansion of one of the fastest-growing companies in sports tech.

Responsibilities:

• Create, validate, and automate sophisticated quantitative models using machine learning, statistics, optimization, and simulation techniques.

• Develop, schedule, monitor, and maintain robust model training and prediction workflows to ensure optimal performance and scalability.

• Work closely with the broader engineering team to implement infrastructure changes that support various sports within our platform.

• Deploy REST APIs on top of fitted models, utilizing distributed computation to enable real-time integration with client-facing applications.

• Provide guidance and technical mentorship to junior engineers, fostering a collaborative and innovative environment.

• Break down complex engineering projects into actionable work plans, assign tasks to engineers and data scientists, and manage timelines effectively.

•  Engage in rotating platform support duties, ensuring the reliability and performance of our machine learning systems.

Requirements:

• Extensive experience in developing and deploying machine learning models, with a strong foundation in statistics, optimization, and simulation.

• Proficiency in designing, developing, and optimizing cloud infrastructure for large-scale, cloud-based analytics systems.

• Fluency in Python (preferred), with experience in R, Scala, or other data-oriented programming languages.

• Hands-on experience with cloud infrastructure and distributed computing, enabling scalable and efficient model deployment.

•  Expertise in relational databases and SQL development, with a focus on efficient data management in large-scale environments.

• Familiarity with Linux servers in virtualized or distributed environments, ensuring stable and secure operations.

• Experience with workflow automation tools such as Airflow, ensuring streamlined and automated processes.

• Proven track record of mentoring junior engineers and fostering a collaborative and growth-oriented team culture.

• Ability to thrive in a rapidly changing technology landscape, continuously learning and adapting to new tools and methodologies.

Desired Traits:

• Takes initiative, proactively manages multiple priorities, and works well under pressure.

• Analytical, creative thinker, and strategic problem-solver.

• Delivers fast but carefully thought-out, high-quality results.