ML OPS AI ENGINEER II
Responsibilities:
• Lead the end-to-end operationalization of machine learning models, moving solutions from experimentation into dependable production environments.
• Develop and support ML infrastructure, automated pipelines, and deployment frameworks that improve reliability and reduce manual effort.
• Create and manage containerized workloads using Docker and coordinate production services through Kubernetes.
• Establish and maintain CI/CD processes for model training, packaging, testing, and release management.
• Implement tools and standards for experiment tracking, feature lineage, and model version control to enable reproducibility.
• Build monitoring solutions that surface system health, model behavior, and data drift, helping teams respond quickly to production issues.
• Provision and optimize cloud and compute resources to support both training and inference workloads effectively.
• Improve scalability, operational visibility, and cost efficiency across deployed AI services.
• Partner with data scientists and ML engineers to simplify deployment pathways and align platform capabilities with model development needs.
Qualifications:
• 3 to 5 years of experience in MLOps, machine learning platform engineering, or AI infrastructure roles.• Demonstrated success deploying, maintaining, and improving machine learning models in production settings.
• Hands-on experience with Azure and managing compute resources for model training and inference.
• Strong background in containerization and orchestration technologies, including Docker and Kubernetes.
• Practical experience building CI/CD pipelines for machine learning or broader software delivery workflows.
• Proficiency in Python, along with experience in automation and infrastructure-as-code practices.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.
• Working knowledge of AI/ML concepts, with the ability to collaborate effectively in a fast-paced, agile environment.
Compensation
$57.47-$66.54 HourlyAbout Us
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