Senior Edge/IoT Engineer

MISSION

SKILLS

• Industrial OT & Machine Data Extraction Deep technical expertise with industrial communication protocols: MTConnect, OPC UA, Modbus (TCP/RTU), MQTT, CAN bus, and Ethernet/IP. Hands-on experience tapping into legacy and modern machine controllers (e.g., Fanuc, Siemens Sinumerik, Haas, Heidenhain, Mazak) via native APIs, industrial ethernet, or hardware taps. Practical understanding of high-frequency machine telemetry extraction (e.g., spindle load, vibration data, axis torque, thermal variation, feed rates, and alarm registers). Edge Systems & Software Engineering High proficiency in C++ (modern C++17/20), Rust , or Python for building efficient, low-latency data ingestion pipelines. Expertise in Linux system administration, custom kernel configuration, real-time operating systems (RTOS), and Linux IPC mechanisms. Deep understanding of edge containerization and orchestration using Docker, podman, K3s, microK8s, or Balena. Experience managing edge device lifecycles (OTA firmware/software updates, secure boot, fleet management, and remote diagnostics). Multimodal Edge AI & Sensor Fusion (Strong Plus) Experience processing and fusing heterogeneous data streams at the edge—combining numerical time-series machine telemetry with visual, thermal, or acoustic inputs. Familiarity with lightweight AI/ML deployment frameworks for edge hardware (ONNX Runtime, TensorRT, OpenVINO, TFLite). Experience optimizing models for edge hardware acceleration (NVIDIA Jetson, Intel OpenVINO, Coral TPUs, or dedicated NPUs). Networking, Security & Shop-Floor Reliability Expertise in store-and-forward architecture, local queuing (e.g., SQLite, Redis, ZeroMQ), and offline-first operational resilience during network drops. Strong grasp of industrial network security: air-gapped systems, VPNs, TLS/mTLS encryption, zero-trust network access.
• Deep technical expertise with industrial communication protocols: MTConnect, OPC UA, Modbus (TCP/RTU), MQTT, CAN bus, and Ethernet/IP.
• Hands-on experience tapping into legacy and modern machine controllers (e.g., Fanuc, Siemens Sinumerik, Haas, Heidenhain, Mazak) via native APIs, industrial ethernet, or hardware taps.
• Practical understanding of high-frequency machine telemetry extraction (e.g., spindle load, vibration data, axis torque, thermal variation, feed rates, and alarm registers).
• High proficiency in C++ (modern C++17/20), Rust , or Python for building efficient, low-latency data ingestion pipelines.
• Expertise in Linux system administration, custom kernel configuration, real-time operating systems (RTOS), and Linux IPC mechanisms.
• Deep understanding of edge containerization and orchestration using Docker, podman, K3s, microK8s, or Balena.
• Experience managing edge device lifecycles (OTA firmware/software updates, secure boot, fleet management, and remote diagnostics).
• Experience processing and fusing heterogeneous data streams at the edge—combining numerical time-series machine telemetry with visual, thermal, or acoustic inputs.
• Familiarity with lightweight AI/ML deployment frameworks for edge hardware (ONNX Runtime, TensorRT, OpenVINO, TFLite).
• Experience optimizing models for edge hardware acceleration (NVIDIA Jetson, Intel OpenVINO, Coral TPUs, or dedicated NPUs).
• Expertise in store-and-forward architecture, local queuing (e.g., SQLite, Redis, ZeroMQ), and offline-first operational resilience during network drops.
• Strong grasp of industrial network security: air-gapped systems, VPNs, TLS/mTLS encryption, zero-trust network access.

COMPETENCIES

Why Foundational