Machine Learning Engineer (ESPN Bet)

Penn Interactive (PI) is an interactive gaming company headquartered in Philadelphia. PI is the digital arm of PENN Entertainment (NASDAQ: PENN), the largest regional casino operator in the U.S.). Our mission is to challenge the norms of the gaming industry by building an immersive interactive gaming experience that is responsible, innovative, and fun. We are committed to helping our team members grow and succeed.  We believe that hiring talented individuals that love what they do will help us win!

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
  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

https://www.linkedin.com/company/penn-interactive-pi/

Recently being recognized as a top workplace in the United States, we believe people work their best when they can be themselves. We are looking for hungry, innovative thinkers to help us challenge the status quo of the gaming industry.  Diversity, equity, and inclusion are vital to all of our processes, programs, and structures. Your story, who you are, and your experience matter here.