Join theScore as a Machine Learning Engineer

theScore, a proud subsidiary of PENN Entertainment, is on a mission to empower millions of sports fans with cutting-edge digital media and sports betting products. Our popular media app 'theScore' delivers highly personalized live scores, news, stats, and betting information to fans across North America. Meanwhile, our sports betting app ‘theScore Bet Sportsbook & Casino’ provides a comprehensive mobile sports betting and iCasino experience, currently live in Ontario. theScore also excels in creating and distributing innovative digital content through web, social, and esports platforms.

About the Role & Team

The Data Science & Machine Learning team is pivotal in enhancing all of PENN Entertainment's digital offerings through advanced models and APIs. Our team thrives on creativity, collaboration, ingenuity, and ownership. As a Machine Learning Engineer, you will have the unique opportunity to contribute, optimize, and deploy various models, as well as develop new features for our machine learning platform.

Ongoing Projects

• Recommendation Engines: Direct users to content they want to see.
• Chat-Toxicity Modelling: Foster an inclusive community chat environment.
• Cross-sell Likelihood: Enable users to explore the full range of PENN Entertainment's offerings.
• Bot User Identification: Combat fraud by identifying non-human users on PENN Entertainment’s digital platforms.

About the Work

As a vital member of our Machine Learning Engineering team, your responsibilities will include:

• Designing and building new machine learning pipelines and optimization routines.
• Deploying models and deliverables in collaboration with functional team leaders and stakeholders across Product, Operations, Marketing, etc.
• Enhancing our machine learning platform by implementing ML ops best practices.
• Conducting thorough testing and evaluation of new tools and technologies to assess their suitability.
• Communicating effectively with both technical and non-technical stakeholders.
• Writing and maintaining technical design and documentation in Git/Confluence.
• Performing other related duties as required.

About You

The ideal candidate will have:

• A minimum of 5 years of professional experience, with at least 3 years as a Machine Learning Engineer.
• A degree in Computer Science, Data Science, Statistics, Computer Engineering, or a related technical field.
• Extensive experience deploying applications using Docker, Kubernetes, Terraform, GitHub, and other relevant tools.
• Proficiency in Python and SQL, with additional knowledge of languages like Go, Rust, Scala, R, and C++ as a plus.
• Proven expertise in setting up CI/CD pipelines for Machine Learning projects, including code, data, and model validation.
• Experience developing machine learning pipelines with orchestration tools such as Airflow, Kubeflow, or Dagster.
• Extensive experience with dbt projects.
• Experience deploying machine learning solutions in public clouds like AWS, Azure, or Google Cloud Platform.
• Familiarity with popular machine learning frameworks such as TensorFlow, PyTorch, Caffe, and Keras.

Nice to Have

• Experience building real-time stream processing solutions using Kafka, Spark, or Flink.
• Experience with virtual feature store technologies like Featureform or Feast.
• Experience integrating with BI tools such as Mode, Tableau, or Looker.
• Background in deploying and monitoring large language models (LLMs).

What We Offer

We believe in offering a supportive and engaging work environment:

• 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

Candidates residing in Ontario requiring special accommodation can email [email protected]

theScore is dedicated to creating a diverse environment and