Machine Learning Engineer

Job Description

PENN Entertainment is seeking a Machine Learning Engineer to join their Data Science & Machine Learning team. This team is responsible for building models and APIs to improve all of Penn Entertainment's digital offerings. The ideal candidate will be passionate about putting machine learning into production and making personalization work at scale.

As a Machine Learning Engineer, the candidate will design, build, and deploy sophisticated machine learning models and infrastructure. This role offers a unique chance to contribute to high-impact projects while helping to advance the company's cutting-edge ML platform.

Role Involves:

• Building and optimizing end-to-end machine learning pipelines from data ingestion to deployment.
• Working closely with Product, Marketing, and Operations teams to align ML solutions with business goals.
• Improving the ML platform and deploy infrastructure using MLOps best practices.
• Evaluating and integrating new tools, models, and frameworks to enhance scalability and performance.
• Clearly communicating technical concepts to both technical and non-technical stakeholders.
• Documenting systems and workflows using Git, Confluence, and related tools.

Requirements:

• 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.
• Experience with Docker, Kubernetes, Terraform, and scalable deployment tools.
• Hands-on experience building CI/CD pipelines for ML systems.
• Proficiency in orchestration tools like Airflow, Kubeflow, or Dagster.
• 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.

What the Role Offers:

• Competitive compensation package
• Fun, relaxed work environment
• Education and conference reimbursements.
• Parental leave top up
• Opportunities for career progression and mentoring others