Machine Learning Ops Engineer

Job Description

• Lead the design, deployment, optimization, and lifecycle management of scalable machine learning infrastructure and ML pipelines.
• Build and maintain workflows for model training, validation, serving, monitoring, drift detection, retraining, and automated alerting.
• Implement ML Ops infrastructure using ML flow, TensorFlow, PyTorch, Docker, Kubernetes, CI/CD, cloud platforms, and infrastructure-as-code practices.
• Ensure production ML systems are secure, reliable, reproducible, governed, documented, and compliant across environments.
• Collaborate with Data Science, Engineering, and DevOps teams, while mentoring junior engineers.
• Requires a bachelor’s degree in a relevant discipline and a minimum of 5 years of hands-on ML solution and ML Ops experience; remote within PA, OH, MI, WV, VA, MD, or NC.