Machine Learning Engineer

Role Overview

You will be a Senior MLOps / DevOps Engineer supporting the development and deployment of enterprise AI/ML platforms. The focus of the role is building and operating scalable Kubernetes-based infrastructure (AWS EKS), enabling ML model deployment, CI/CD automation, and reliable platform operations.

Responsibilities

• Design, build, and support Kubernetes-based platforms for AI/ML workloads (EKS)
• Implement and manage CI/CD pipelines for ML and application deployments
• Support ML model deployment, versioning, and lifecycle management
• Collaborate with data science and engineering teams to enable scalable ML solutions
• Troubleshoot and resolve platform and deployment issues
• Improve reliability, performance, and scalability of systems
• Drive automation and infrastructure improvements
• Support integrations with data platforms (Databricks, Snowflake, or similar)

Requirements

• 6+ years of experience in DevOps, Platform Engineering, or related fields
• Strong hands-on Kubernetes expertise (EKS preferred)
• Experience building and managing CI/CD pipelines
• Exposure to or experience with MLOps and ML lifecycle management
• Experience deploying applications/services in cloud environments (AWS preferred)
• Strong scripting and automation skills
• Understanding of system reliability, scalability, and performance optimization

Nice to Have

• Experience with Databricks (preferred) or Snowflake/other data platforms
• Familiarity with monitoring and observability tools