MLOps Engineer
Trunk ToolsFull Time
Junior (1 to 2 years)
Candidates should have 3+ years of professional experience as a Machine Learning Engineer or in a similar role, with a background in Computer Science, Data Science, Engineering, or a related technical field. Strong programming skills in Python and SQL are required, with bonus points for Go, Rust, Scala, R, or C++. Experience with Docker, Kubernetes, Terraform, scalable deployment tools, and building CI/CD pipelines for ML systems is essential.
The Machine Learning Engineer will design, build, and deploy sophisticated machine learning models and infrastructure to improve user engagement and satisfaction across digital offerings. Responsibilities include building and optimizing end-to-end machine learning pipelines, working with cross-functional teams to align ML solutions with business goals, improving the ML platform using MLOps best practices, evaluating and integrating new tools and frameworks, and clearly communicating technical concepts to stakeholders. The role also involves documenting systems and workflows using Git and Confluence.
Develops online sportsbooks and casino games
Penn Interactive specializes in developing online sportsbooks, casinos, and free-to-play gaming experiences, utilizing cutting-edge technologies to deliver immersive sports betting experiences and enhance the overall gaming experience. The company leverages advanced technologies to provide a seamless and engaging gaming experience, including innovative features for sports betting and casino gaming.