Machine Learning Engineer - Remote

Overview

PENN Entertainment, Inc. is North America’s leading provider of integrated entertainment, sports content, and casino gaming experiences. From casinos and racetracks to online gaming, sports betting and entertainment content, we deliver the experiences people want, how and where they want them.

We’re always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether it’s through ESPN BET, Hollywood Casino, theScore Bet Sportsbook & Casino, or theScore media app, we’re excited to push the boundaries of what’s possible. These state-of-the-art platforms are powered by proprietary in-house technology, a key component of PENN’s omnichannel gaming and entertainment strategy.

When you join PENN Entertainment’s digital team, you’ll not only work on these cutting-edge platforms through theScore and PENN Interactive, but you’ll also be part of a company that truly cares about your career growth. We’re committed to supporting you as you expand your skills and explore new opportunities.

With locations throughout North America, you can build a future at PENN Entertainment wherever you are. If you want to challenge conventions in gaming, media and entertainment, we want to talk to you.

In Short

• Design, build, and deploy machine learning models.
• Enhance user engagement through personalized recommendation engines.
• Implement chat toxicity detection using NLP.
• Conduct cross-sell propensity modeling.
• Support dynamic personalization efforts.
• Collaborate with various teams to align ML solutions with business goals.
• Optimize end-to-end machine learning pipelines.
• Document systems and workflows effectively.
• Work with cloud environments and orchestration tools.
• Contribute to high-impact projects in machine learning.

Requirements

• 3+ years of experience as a Machine Learning Engineer or similar role.
• Background in Computer Science, Data Science, Engineering, or a related field.
• Strong programming skills in Python and SQL.
• Experience with Docker, Kubernetes, and Terraform.
• Hands-on experience building CI/CD pipelines for ML systems.
• Proficiency in orchestration tools like Airflow or Kubeflow.
• Comfort working in cloud environments like AWS, GCP, or Azure.
• Familiarity with ML frameworks such as PyTorch or TensorFlow.
• Ability to communicate technical concepts to diverse stakeholders.
• Experience with real-time personalization systems is a plus.

Benefits

• Competitive compensation package.
• Fun, relaxed work environment.
• Education and conference reimbursements.
• Parental leave top-up.
• Opportunities for career progression and mentoring.