Machine Learning Engineer – Coop

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