Lead Engineer, MLOps

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Requirements:

• Extensive experience in deploying machine learning models to cloud environments.
• Strong expertise in Docker container orchestration.
• Proficiency in Terraform for infrastructure as code (IaC) and cloud resource management.
• Hands-on experience with streaming data platforms like Kafka and Kinesis.
• Solid understanding of data cleaning, transformation, and ETL processes.
• Experience with CI/CD tools and pipelines such as Jenkins and GitLab CI.
• Strong programming skills in Python; familiarity with ML frameworks like TensorFlow and PyTorch is a plus.
• Excellent problem-solving skills and critical thinking.
• Strong communication skills to convey technical concepts to non-technical stakeholders.

Responsibilities:

• Design and implement MLOps pipelines to ensure consistency across the organization.
• Configure and manage cloud-based resources to support AI/ML workloads.
• Automate model deployment and management through scripts and tools.
• Collaborate with data scientists and engineers to tailor MLOps solutions.
• Monitor and optimize AI/ML infrastructure performance.
• Stay up-to-date with industry trends and improve MLOps capabilities.