Senior Machine Learning Engineer, Platform
Philadelphia, PA
Full Time Senior-level / Expert USD 140K - 200K
Penn Interactive
PENN Entertainment, Inc. is North Americaâs 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.
Weâre always on the lookout for those who are passionate about creating and delivering cutting-edge online gaming and sports media products. Whether itâs through ESPN BET, Hollywood Casino, theScore Bet Sportsbook & Casino, or theScore media app, weâre excited to push the boundaries of whatâs possible. These state-of-the-art platforms are powered by proprietary in-house technology, a key component of PENNâs omnichannel gaming and entertainment strategy.
When you join PENN Entertainmentâs digital team, youâll not only work on these cutting-edge platforms through theScore and PENN Interactive, but youâll also be part of a company that truly cares about your career growth. Weâre committed to supporting you as you expand your skills and explore new opportunities.
With locations throughout North America, you can build a future at PENN Entertainment wherever you are. If you want to challenge conventions in gaming, media and entertainment, we want to talk to you.
About the Role & TeamâŻ
The Machine Learning Platform team at Penn Entertainment builds the infrastructure, tools, and frameworks that power our machine learning lifecycleâfrom training and deployment to monitoring and optimization. As a Machine Learning Engineer, youâll play a key role in scaling and evolving our ML platform. Youâll work closely with data scientists, ML engineers, and data engineers to design robust, efficient, and production-grade systems that accelerate ML innovation across the company.Â
This is a hands-on engineering role focused on creating the foundational systems that support the development, deployment, and operation of machine learning models at scale.Â
About the WorkâŻÂ
- Design, build, and maintain core components of the ML platform including model serving infrastructure, feature stores, and monitoring systems.
- Develop and maintain CI/CD pipelines for ML workflows to support reproducibility, scalability, and continuous delivery of models.
- Collaborate with ML engineers and data scientists to support model experimentation, packaging, and deployment in both batch and real-time contexts.
- Contribute to the development of best practices for MLOps, including versioning, lineage tracking, observability, and governance.
- Write clean, testable, and well-documented code and contribute to team knowledge through documentation and design reviews.
- Partner with data engineering and platform teams to ensure seamless integration with data pipelines and compute environments.
About YouÂ
- Experience: 5+ years of experience in machine learning engineering, data engineering, or backend software engineering, with demonstrated experience building ML systems in production.
- Technical Skills: Proficiency in Python and SQL. Deep familiarity with cloud platforms such as GCP, AWS, or Azure.
- MLOps & Infrastructure: Hands-on experience with ML model deployment, CI/CD pipelines, containerization (Docker, Kubernetes), and orchestration tools (Dagster, Airflow, Kubeflow, or similar).
- ML Tooling: Experience with model packaging and serving technologies such as MLflow, Seldon, Vertex AI, or AWS SageMaker.
- Collaboration: Strong communication skills and a desire to work cross-functionally with data scientists, ML engineers, and platform teams.
- Education: Bachelorâs or Masterâs degree in Computer Science, Engineering, or a related technical field.
Nice to haveÂ
- Exposure to large language models (LLMs) and their deployment considerations.
- Familiarity with monitoring, observability, and alerting tools for ML systems.
- Contributions to open-source MLOps tooling or platforms.
What We OfferâŻ:Â
- Competitive compensation packageâŻ
- Fun, relaxed work environmentâŻ
- Education and conference reimbursements.âŻ
- Parental leave top upâŻ
- Opportunities for career progression and mentoring othersâŻÂ
#LI-REMOTE
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Salary Range$140,000â$200,000 USDInitial placement within the salary range is based on an individual's relevant knowledge, skills, and experience. Base salary is just one component of our competitive Total Rewards package, which includes wellness programs designed to support our team members' financial, physical, and mental well-being. Specific benefitsâsuch as day-one medical coverage, 401(k) matching, annual performance bonus and equity package â depending on position. Paid time off is earned according to the local policy and increases with the length of employment.
Click HERE to discover how we empower team members to grow, thrive, and advance in their careers. Check out our LinkedIn page!
Tags: Airflow AWS Azure CI/CD Computer Science Dagster Data pipelines Docker Engineering GCP Kubeflow Kubernetes LLMs Machine Learning MLFlow ML models MLOps Model deployment Open Source Pipelines Python SageMaker Seldon SQL Vertex AI
Perks/benefits: Career development Competitive pay Equity / stock options Health care Medical leave Parental leave Salary bonus Wellness
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