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.
Work-term: January 5, 2026 - April 24, 2026
Number of Openings: 1
About the Role & Team
The Data Science & Machine Learning team is responsible for building models and APIs to help improve all of Penn Entertainment's digital offerings. Our team values creativity, collaboration, ingenuity, and ownership. As a machine learning engineer, you will get the opportunity to contribute to, optimize, and deploy many exciting models as well as help the team build net-new features into our machine learning platform.
Examples of some of our on-going projects:
- Recommendation engines: we want to direct users to content they want to see.
- Experimentation frameworks: we want to understand the impact our products have on users
- Chat-Toxicity Modelling: create an inclusive community chat environment.
- Cross-sell Likelihood: enable users to access the full range of Penn
Entertainment's offerings. - Bot User Identification: fight fraud on Penn Entertainment’s digital offerings by
identifying non-human users
About the Work
As a key member of our Machine Learning Engineering team, you will:
- Assist in the design and development of new machine learning pipelines
- Help deploy models and deliverables in conjunction with functional team leaders and stakeholders (in Product, Operations, Marketing, etc.)
- Improve our machine learning platform by implementing ML ops best practices.
- Conduct thorough testing and evaluation of new tools and technologies to assess their suitability for our platform.
- Communicate clearly and efficiently with technical and non-technical stakeholders.
- Write and maintain technical design and git/Confluence documentation.
- Other duties as required.
About You
- Currently enrolled in a university degree in Computer Science, Data Science, Statistics, Computer Engineering, or a related technical field.
- Experience in deploying applications using Docker, Kubernetes, Terraform, GitHub and other relevant tools.
- Proficient with Python and SQL. Languages like Go, Rust, Scala, R, and C++ are nice-to-have.
- Proven expertise in setting up Continuous Integration/Continuous Deployment (CI/CD) pipelines for Machine Learning projects. Skilled in testing and validating code, data, data schemas, and models.
- Demonstrated experience developing machine learning pipelines with orchestration tools like Airflow, Kubeflow, or Dagster.
- Extensive experience building and/or contributing to dbt projects.
- Experience developing and deploying machine learning solutions in a public cloud such as AWS, Azure, or Google Cloud Platform is preferred.
- Familiarity with popular machine learning frameworks such as TensorFlow,
PyTorch, Caffe, and/or Keras
Nice To Have
- Experience building real-time stream processing solutions with technologies such as Kafka, Spark, and Flink.
- Experience with virtual feature store technologies such as Featureform or Feast.
- Experience integrating with BI tools such as Mode, Tableau, Looker, or
- Background in deploying and monitoring large language models (LLMs).
What We Offer:
- Fun, relaxed work environment
- A voice. We're dedicated to open communication which empowers our employees to drive the company's culture
- A company that encourages a culture of inclusion and diversity
- Opportunity to work on large-scale consumer-facing applications with millions of users
Candidates residing in Ontario requiring special accommodation can email accessibilityoffice@thescore.com
Penn Interactive is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability or age.