Machine Learning Engineer

1 month ago

Toronto ON, Canada Score Media and Gaming Inc. Full time

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 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
    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

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