theScore, a wholly-owned subsidiary of PENN Entertainment , empowers millions of sports fans through its digital media and sports betting products. Its media app ‘theScore’ is one of the most popular in North America, delivering fans highly personalized live scores, news, stats, and betting information from their favorite teams, leagues, and players. theScore’s sports betting app ‘theScore Bet Sportsbook & Casino’ delivers an immersive and holistic mobile sports betting and iCasino experience. theScore Bet is currently live in the Company's home province of Ontario. theScore also creates and distributes innovative digital content through its web, social and esports platforms.

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 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.
  • 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:

  • Design and build new machine learning pipelines and optimization routines.
  • Deploy modes 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

  • A minimum of 5 years of professional experience, 3 as a Machine Learning Engineer
  • A degree/background in Computer Science, Data Science, Statistics, Computer
    Engineering, or a related technical field.
  • Extensive 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
  • 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

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



Candidates residing in Ontario requiring special accommodation can email

theScore 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.


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