Senior Machine Learning Ops Engineer

Job Summary

To operationalize machine learning solutions at scale, the full-time Senior Machine Learning Ops Engineer will lead the design, deployment, and optimization of ML infrastructure and pipelines while working remotely within a seven-state footprint.

Key responsibilities

• Lead the end-to-end development and optimization of ML pipelines, including training, validation, deployment, monitoring, and retraining workflows at scale
• Guide the implementation of infrastructure for tools such as ML flow, TensorFlow, PyTorch, Docker, and Kubernetes to support scalable production workflows
• Design and monitor tools for performance monitoring, drift detection, and automated alerting to ensure continuous model performance

Required qualifications

• Bachelor's degree in Computer Science, Management Information Systems, Computer Engineering, or a related discipline
• Minimum 5 years of hands-on experience in designing, developing, and operationalizing machine learning solutions with a focus on ML Ops practices
• Experience managing machine learning pipelines, lifecycle management, and deployment at scale, including training, validation, serving, and monitoring
• Familiarity with CI/CD pipelines for ML workflows and containerization tools such as Docker and Kubernetes
• Experience with secure and scalable cloud environments (e.g., AWS, GCP, Azure) and infrastructure-as-code offerings