Edge Deployment Engineer (DevOps / Edge Infrastructure)

OverviewEdge Deployment Engineer (DevOps / Edge Infrastructure) — On-site onlyWe 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.Key ResponsibilitiesDeploy and operate pre-trained ML models and supporting services on customer edge devicesDesign and implement deployment scaffolding to package customer-provided servicesSupport edge infrastructure design, including:Hardware recommendationsCapacity planningPerformance optimizationStandardize and streamline deployment processes across customer environmentsIntegrate data from cameras, sensors, and existing factory systems using established interfacesCollaborate directly with client teams on-site to troubleshoot and improve deploymentsEnsure solutions are reliable, maintainable, and easy to deploy at scaleRequired Qualifications (Must-Haves)Strong DevOps engineering backgroundExperience deploying services to edge or on-prem environmentsProficiency in Python for development and deployment supportExperience with containers and service packagingAbility to perform light development work in addition to DevOps tasksComfortable working in manufacturing or industrial environmentsStrong communication skills; client-facing experience requiredLocal to Georgetown / Lexington areaPreferred (Nice-to-Have)Familiarity with ML / MLOps concepts (no model development required)Exposure to PLC, MES, or factory systems at a high levelExperience working with industrial cameras, sensors, or edge compute devicesBackground in system integration or deployment engineeringJ-18808-Ljbffr