Description

You will lead the development and deployment of ML model interfaces for real-time fault detection in laser welding.

Responsibilities

• 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 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 with Terraform, and DevSecOps practices.

Required Skills

• 5+ years of experience in industrial system integration (PLCs, industrial PCs, OT/IT network architectures).
• Experience with machine learning deployment and real-time inference in manufacturing.
• Proficiency in Ignition (Perspective & Edge) and MQTT (HiveMQ).
• Hands-on experience with Docker containerization and edge computing.
• Strong background in data pipeline design and sensor data processing.
• Experience with AWS IoT Greengrass, AWS IoT Core, S3, DataSync, or Storage Gateway.
• Knowledge of Databricks and infrastructure automation using Terraform.
• Proficiency with CI/CD tools including CodeBuild and ECR.
• Experience with PostgreSQL databases.

Preferred Skills

• Experience with GPU accelerated ML models and deployments to NVIDIA hardware.
• Knowledge of AWS SageMaker and media metadata management.
• Experience with laser welding or automated manufacturing processes.

Key Skills

Education

Any Gradute