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Are you passionate about powering real-time AI and analytics at the intersection of devices, data, and the cloud? Our fast-growing, innovative SaaS fast GTM fast growing, industry disruptor is seeking an experienced IoT Edge AI Data Engineer to architect and build the next generation of edge-to-cloud data pipelines supporting sensor-driven platforms. You’ll be working with cutting-edge edge hardware, including NVIDIA Jetson, and developing solutions that transform raw sensor data into powerful, ML-ready streams and data pipelines.
Job Responsibility:
Design & implement high volume data ingestion pipelines for IoT systems, from device through on-prem infrastructure to cloud platforms
Develop edge computing solutions leveraging platforms like NVIDIA Jetson for near-real-time data processing, orchestration, & distribution
Build robust frameworks to clean, validate, and prepare sensor, telemetry, and machine data for downstream ML engineering teams
Architect and software engineer, infrastructure for reliable edge-to-cloud connectivity and data workflows
Optimize on-prem and distributed data flows for scalable, resilient performance
Requirements:
3–4+ years of data engineering experience—MUST designing and deploying device-to-cloud pipelines for IoT/edge environments
Hands-on experience with edge hardware (e.g., NVIDIA Jetson) and low-level data engineering
Proficient in cloud data services, streaming, and orchestration (AWS, Azure, GCP, Kinesis, MQTT, Kafka, etc.)
Data cleansing, data ingestion, and data engineering dealing with getting data OFF OF Edge devices
Strong software engineering skills: Python, C++
Deep knowledge of sensor/telemetry data and proven capability in building scalable data infrastructure for ML/AI use cases
Experience with on-premises distributed systems & cloud integration
Prior work with edge AI or industrial IoT, developing robust real-time data pipelines
hardware/software integration
What we offer:
medical, vision, dental, and life and disability insurance