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 :
Entertainment's offerings.
identifying non-human users
About the Work
As a key member of our Machine Learning Engineering team, you will :
stakeholders (in Product, Operations, Marketing, etc.)
assess their suitability for our platform.
technical stakeholders.
About You
Engineering, or a related technical field.
Terraform, GitHub and other relevant tools.
nice-to-have.
CI / CD) pipelines for Machine Learning projects. Skilled in testing and validating
code, data, data schemas, and models.
orchestration tools like Airflow, Kubeflow, or Dagster.
cloud such as AWS, Azure, or Google Cloud Platform is preferred.
PyTorch, Caffe, and / or Keras
Nice to Have
as Kafka, Spark, and Flink.
What We Offer
LI-REMOTE #LI-HYBRID
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.