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    Machine Learning Engineer - Toronto, Canada - theScore

    theScore
    theScore Toronto, Canada

    3 weeks ago

    Default job background
    Description

    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.

    About You

    • A minimum of 3 years of professional experience as a Machine Learning
    • 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
      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

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

    #LI-REMOTE #LI-HYBRID

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