Machine Learning Engineer (Coop) W2026
Machine Learning Engineer (Coop) W2026
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Job Description
PENN Entertainment Inc. is North Americas 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.
Were always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether its through ESPN BET Hollywood Casino theScore Bet Sportsbook & Casino or theScore media app were excited to push the boundaries of whats possible. These state-of-the-art platforms are powered by proprietary in-house technology a key component of PENNs omnichannel gaming and entertainment strategy.
When you join PENN Entertainments digital team youll not only work on these cutting-edge platforms through theScore and PENN Interactive but youll also be part of a company that truly cares about your career growth. Were 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 Entertainments digital offerings. Our team values creativity collaboration ingenuity and 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 PennEntertainments offerings.
- Bot User Identification: fight fraud on Penn Entertainments digital offerings byidentifying 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 toassess their suitability for our platform.
- Communicate clearly and efficiently with technical and non-technicalstakeholders.
- 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 KubernetesTerraform GitHub and other relevant tools.
- Proficient with Python and SQL. Languages like Go Rust Scala R and C arenice-to-have.
- Proven expertise in setting up Continuous Integration/Continuous Deployment(CI/CD) pipelines for Machine Learning projects. Skilled in testing and validatingcode data data schemas and models.
- Demonstrated experience developing machine learning pipelines withorchestration tools like Airflow Kubeflow or Dagster.
- Extensive experience building and/or contributing to dbt projects.
- Experience developing and deploying machine learning solutions in a publiccloud 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. Were dedicated to open communication which empowers our employees to drive the companys 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
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.
Employment Type
Full Time
