Edge Deployment Engineer; DevOps​/Edge Infrastructure

Overview

Edge Deployment Engineer (Dev Ops / Edge Infrastructure) — On-site only

We are seeking an Edge Deployment Engineer to support the deployment of pre-built, pre-trained machine learning solutions onto customer edge devices in a manufacturing environment. This role is not focused on building or training ML models
. Instead, it centers on deploying, packaging, and operationalizing existing services close to production systems and optimizing them for performance, reliability, and ease of deployment.

This is a client-facing, hands-on role
, working directly on-site with customer teams.

• Deploy and operate pre-trained ML models and supporting services on customer edge devices
• Design and implement deployment scaffolding to package customer-provided services
• Support edge infrastructure design
  , including:
• Hardware recommendations
• Capacity planning
• Performance optimization
• Standardize and streamline deployment processes across customer environments
• Integrate data from cameras, sensors, and existing factory systems using established interfaces
• Collaborate directly with client teams on-site to troubleshoot and improve deployments
• Ensure solutions are reliable, maintainable, and easy to deploy at scale

• Strong Dev Ops engineering background
• Experience deploying services to edge or on-prem environments
• Proficiency in Python for development and deployment support
• Experience with containers and service packaging
• Ability to perform light development work in addition to Dev Ops tasks
• Comfortable working in manufacturing or industrial environments
• Strong communication skills;
  client-facing experience required
• Local to Georgetown / Lexington area

• Familiarity with ML / MLOps concepts (no model development required)
• Exposure to PLC, MES, or factory systems at a high level
• Experience working with industrial cameras, sensors, or edge compute devices
• Background in system integration or deployment engineering