Machine Learning Engineer (Fully Remote)
Score Media and Gaming Inc.
PENN Entertainment, Inc. is North America's leading provider of integrated entertainment, sports content, and casino gaming experiences. From casinos and racetracks to online gaming, sports betting and entertainment content, we deliver the experiences people want, how and where they want them.
We're always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether it's through ESPN BET, Hollywood Casino, theScore Bet Sportsbook & Casino, or theScore media app, we're excited to push the boundaries of what's possible. These state-of-the-art platforms are powered by proprietary in-house technology, a key component of PENN's omnichannel gaming and entertainment strategy.
When you join PENN Entertainment's digital team, you'll not only work on these cutting-edge platforms through theScore and PENN Interactive, but you'll also be part of a company that truly cares about your career growth. If you want to challenge conventions in gaming, media and entertainment, we want to talk to you.
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. As a Machine Learning Engineer, you'll be instrumental in crafting the next generation of user experiences. You will design, build, and deploy sophisticated machine learning models and infrastructure that directly impact how users discover content, engage with our community, and explore the full spectrum of Penn Entertainment's offerings. This role offers a unique chance to contribute to high-impact projects while helping to advance our cutting-edge ML platform.
About the Work We're focused on projects that directly improve user engagement and satisfaction. Personalized Recommendation Engines - Help users discover the games, promotions, and content they care about most through behavioral, contextual, and collaborative filtering models.
Chat Toxicity Detection - Ensure a safe and welcoming community environment with NLP-based classification.
Dynamic Personalization - Enable real-time decision-making in product features, content feeds, and user journeys using machine learning.
You'll also be instrumental in scaling our ML platform to support these future efforts.
As part of the Machine Learning Engineering team, you will:
Build and optimize end-to-end machine learning pipelines from data ingestion to deployment.
Work closely with Product, Marketing, and Operations teams to align ML solutions with business goals.
Improve our ML platform and deploy infrastructure using MLOps best practices.
Evaluate and integrate new tools, models, and frameworks to enhance scalability and performance.
Clearly communicate technical concepts to both technical and non-technical stakeholders.
You're someone who's passionate about putting machine learning into production and making personalization work at scale. 3+ years of professional experience as a Machine Learning Engineer or in a similar role.
- A background in Computer Science, Data Science, Engineering, or a related technical field.
- Strong programming skills in Python and SQL. Bonus for Go, Rust, Scala, R, or C++.
- Experience with Docker, Kubernetes, Terraform, and scalable deployment tools.
- Hands-on experience building CI/CD pipelines for ML systems.
- Experience working on or contributing to dbt projects.
- Comfort working in cloud environments like AWS, GCP, or Azure.
- Familiarity with ML frameworks such as PyTorch, TensorFlow, Keras, or similar.
Experience building real-time personalization or recommendation systems at scale.
Familiarity with virtual feature stores like Feast or Featureform.
Exposure to working with or deploying large language models (LLMs) in production.
Education and conference reimbursements.
Parental leave top up
Opportunities for career progression and mentoring others #LI-REMOTE
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.
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