Senior Industrial Vision Platform Engineer (devops / Mlops Focus)

Senior Industrial Vision Platform Engineer (DevOps / MLOps Focus)

Employment Type: Full-Time (Permanent) OR Contract

Location: Remote within the U.S. + Travel (2–3 times per month to manufacturing sites in Georgetown KY)

Role Overview

We are seeking a Senior Industrial Vision Platform Engineer with strong DevOps and MLOps ownership to design, build, and operate cloud-native computer vision platforms supporting automotive and industrial manufacturing environments.

This role is platform-first , not an algorithm-only position. The ideal candidate has hands-on experience operationalizing computer vision systems at scale , owning CI/CD pipelines, cloud infrastructure, model deployment, monitoring, and reliability across multiple production environments.

You will work closely with ML engineers, manufacturing teams, and IT stakeholders to ensure vision solutions are scalable, reliable, secure, and production ready .

Key Responsibilities

• Architect, build, and operate cloud-native industrial vision platforms supporting real-time and batch image/video processing workloads.
• Own DevOps and MLOps pipelines for computer vision systems, including build, test, deployment, monitoring, rollback, and version control.
• Design and maintain AWS-based infrastructure for ML workloads using services such as EC2, S3, EKS/ECS, Lambda, and SageMaker.
• Implement CI/CD pipelines for ML models and platform services using modern DevOps tooling.
• Manage containerized workloads using Docker and Kubernetes in production environments.
• Establish Infrastructure as Code (IaC) practices using Terraform or CloudFormation.
• Enable end-to-end ML lifecycle management , including model packaging, deployment, performance monitoring, and drift detection.
• Integrate vision platforms with manufacturing systems such as PLCs, MES, and plant data pipelines.
• Ensure platform reliability through observability, logging, alerting, and incident response best practices.
• Collaborate with ML and vision engineers to transition models from development into stable, scalable production systems.
• Support deployments across multiple manufacturing plants and environments.

Required Qualifications

• 7+ years of professional software engineering experience with senior-level technical ownership.
• Strong proficiency in Python for backend services, automation, and ML workflows.
• Hands-on experience with cloud-native architecture on AWS , including:
• EC2, S3, IAM, VPC
• EKS or ECS
• SageMaker or equivalent ML services
• Proven experience building and operating CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar).
• Strong experience with Docker and Kubernetes in production environments.
• Solid understanding of DevOps and MLOps practices , including model versioning, deployment, rollback, and monitoring.
• Practical experience supporting computer vision or ML systems in production .
• Experience delivering systems in manufacturing, automotive, or industrial environments .

Nice to Have

• Experience with industrial computer vision use cases such as quality inspection, defect detection, or traceability.
• Exposure to edge or hybrid cloud deployments .
• Knowledge of industrial protocols such as OPC UA, MQTT, or Modbus .
• Familiarity with observability tools for ML systems (metrics, logs, alerts).
• Prior experience supporting multi-plant or globally distributed platforms .

What This Role Is NOT

• ❌ Not an algorithm-only computer vision role
• ❌ Not a research-focused ML position
• ❌ Not an embedded firmware or hardware-tuning role

This position focuses on platform ownership, DevOps, and operational excellence for industrial vision systems.