Lead and mentor a team of MLOps engineers to design, develop, and maintain scalable machine learning infrastructure and deployment pipelines.
Collaborate cross-functionally with data scientists, software engineers, and product teams to operationalize ML models and ensure robust, reliable production systems.
Drive best practices in CI/CD, automation, monitoring, and cloud infrastructure management specific to ML workflows.
Serve as a technical expert and functional lead in MLOps, influencing architecture decisions and technology adoption.
Contribute to strategic planning and continuous improvement of ML lifecycle management processes.
Requirements
3+ years of relevant / direct industry experience
Bachelor's degree in Computer Science or related field
Experience with machine learning infrastructure and deployment pipelines
Proficiency in Python (Programming Language)
Experience with cloud infrastructure and CI/CD frameworks
Must be familiar with Docker and Kubernetes.
Tech Stack
Cloud
Docker
Kubernetes
Python
Benefits
medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service