Engineering Manager, ML Platform

Job Description

PENN Entertainment is seeking an Engineering Manager to lead its Machine Learning Platform team. This role involves driving the vision, strategy, and execution of the machine learning platform, ensuring alignment with data science and machine learning deliverables. The Engineering Manager will hire, mentor, and lead a team of ML platform engineers, fostering professional growth and a culture of innovation. They will oversee the development of scalable ML infrastructure, model serving, feature stores, and monitoring systems. This role involves partnering with stakeholders across data engineering, ML engineering, and data product teams to enable the development of robust ML pipelines and integrations. The Engineering Manager will establish and improve MLOps best practices, ensuring robust CI/CD pipelines, model monitoring, and efficient resource utilization. They will also assess and recommend new tools, frameworks, and technologies to improve the efficiency and effectiveness of machine learning solutions. The role requires maintaining technical design documents and ensuring knowledge sharing across the team.Responsibilities:

• Drive the vision, strategy, and execution of the machine learning platform.
• Hire, mentor, and lead a team of ML platform engineers.
• Oversee the development of scalable ML infrastructure.
• Partner with stakeholders across data engineering, ML engineering, and data product teams.
• Establish and improve MLOps best practices.
• Assess and recommend new tools, frameworks, and technologies.
• Maintain technical design documents and ensure knowledge sharing.

Requirements:

• 3+ years of professional experience in machine learning, data engineering, or software engineering.
• 2+ years in a leadership or managerial role.
• Strong background in machine learning infrastructure, data engineering, and software development.
• 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.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

The role offers:

• Opportunity to lead a talented team of engineers.
• Chance to drive the vision and strategy of the machine learning platform.
• Work on cutting-edge technologies and tools.
• Professional growth and a culture of innovation.