Senior Industrial IoT Engineer

Key Responsibilities:

• Lead development and deployment of ML model interfaces for real-time fault detection in laser welding.
• Configure and integrate Ignition Perspective, MQTT brokers (HiveMQ), and PostgreSQL databases across plant and DMZ networks.
• Manage data pipelines, dashboards, and historian setups to visualize key machine metrics and inference results.
• Oversee edge deployments using NVIDIA hardware, Docker containers, and AWS IoT Greengrass.
• Build and maintain secure, scalable MQTT bridges between cloud and plant networks.
• Implement automated CI/CD pipelines, infrastructure provisioning (Terraform), and DevSecOps best practices.
• Collaborate across cloud, OT, data science, and engineering teams to deliver end-to-end solutions.

Essential Skills:

• Industrial system integration expertise (PLCs, industrial PCs, OT/IT network architectures).
• Experience with machine learning deployment and real-time inference in manufacturing environments.
• Proficiency in Ignition (Perspective & Edge) and MQTT (HiveMQ).
• Containerization with Docker and edge computing
• Strong background in data pipeline design, image/media handling, and sensor data processing.

Preferred / Nice to Have:

• Experience with laser welding or automated manufacturing processes.
• Knowledge of AWS SageMaker, and media metadata management.
• Familiarity with DevSecOps principles and secure industrial network configurations.
• Leadership experience managing small cross-functional teams.
• Cloud services: AWS IoT Greengrass, AWS IoT Core, S3, DataSync or Storage Gateway and Databricks.
• Infrastructure automation using Terraform and CI/CD tools (CodeBuild, ECR).
• Optional previous experience with GPU accelerated Machine Learning Models and deployments to Nvidia hardware