Engineering Manager, ML Platform

Summary

Join PENN Entertainment's digital team as the Engineering Manager of the ML Platform and lead a team of engineers in building and maintaining the infrastructure for data science and machine learning initiatives. You will drive the vision and strategy of the machine learning platform, ensuring alignment with company deliverables. Responsibilities include hiring and mentoring a team, overseeing the development of scalable ML infrastructure, partnering with stakeholders, establishing MLOps best practices, and recommending new tools and technologies. The ideal candidate possesses 3+ years of experience in machine learning, data engineering, or software engineering, with at least 2 years in a leadership role, along with a strong background in machine learning infrastructure and proficiency in Python, SQL, and cloud platforms. A Bachelor's or Master's degree in a related field is required. PENN Entertainment offers a supportive environment for career growth and various locations throughout North America.

Requirements

• 3+ years of professional experience in machine learning, data engineering, or software engineering, with at least 2 years in a leadership or managerial role
• Strong background in machine learning infrastructure, data engineering, and software development, with proficiency in Python, SQL, and cloud platforms (GCP, AWS, Azure)
• Experience with machine learning packaging and serving patterns and related tooling (MLflow, Seldon, Kserve, Vertex, AWS SageMaker)
• Hands-on experience with CI/CD pipelines, containerization (Docker, Kubernetes), and orchestration tools (Airflow, Kubeflow, or Dagster)
• Ability to communicate complex technical concepts to non-technical stakeholders and lead a high-performing team
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field

Responsibilities

• Drive the vision, strategy, and execution of the machine learning platform, ensuring alignment with data science and machine learning deliverables at the company
• Hire, mentor, and lead a team of ML platform engineers, fostering professional growth and a culture of innovation
• Oversee the development of scalable ML infrastructure, model serving, feature stores, and monitoring systems
• Partner with stakeholders across data engineering, ML engineering, and data product teams to enable the development of robust ML pipelines and integrations
• Establish and improve MLOps best practices, ensuring robust CI/CD pipelines, model monitoring, and efficient resource utilization
• Assess and recommend new tools, frameworks, and technologies to improve the efficiency and effectiveness of machine learning solutions
• Maintain technical design documents, Git/Confluence documentation, and ensure knowledge sharing across the team

Preferred Qualifications

• Experience with real-time stream processing and virtual feature stores (Featureform, Feast)
• Background in deploying and monitoring large language models (LLMs)
• Familiarity with BI tools such as Tableau, Looker, or Mode

Benefits

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