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# Embedded Edge AI Architect

- **Company:** Trebecon LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Data Validation, Information Engineering, Data Infrastructure, Linux on Embedded Systems, Firmware, Field-Programmable Gate Array (FPGA), FreeRTOS, Python (Programming Language), Multipoint Control Unit, Performance Tuning, Real-Time Operating Systems, DataOps, Application Data, Signal Processing, Software Engineering, Data Processing, Graphics Processing Unit (GPU), Cloud Platform System, High Performance Computing, Delivery Pipeline, Real Time Data, Data Pipelines
- **Published:** June 30, 2026
- **Apply:** https://www.dice.com/job-detail/db94190c-312e-4832-84ff-cb906c3f6765

## About the Role

· 8-10+ years of experience in data engineering, telemetry systems, or applied data science within embedded, edge, or hardware-adjacent environments
· Strong proficiency in Python for data processing, modeling, and pipeline development
· Working knowledge of C/C++ to interface with low-level systems and firmware integration points
· Proven experience designing and building telemetry pipelines, data models, and ingestion frameworks
· Experience translating hardware/firmware signals into structured datasets for analytics, performance tuning, or ML use cases
· Strong understanding of time-series data, signal processing, and real-time data constraints
· Experience building firmware-to-application data interfaces and ingestion pathways
· Ability to operate across system layers: device/edge * transport * host * data platform
· Familiarity with GPU-based systems or high-performance computing environments
· Strong cross-functional collaboration with firmware, hardware, and platform engineering teams
· Experience designing performance characterization and optimization models that correlate telemetry, workload behavior, thermal constraints, and system utilization into actionable tuning policies, workload mappings, and system-level control decisions
· Experience with edge AI / inference pipelines or GPU-accelerated workloads
· Familiarity with RTOS concepts (Zephyr, FreeRTOS) - awareness vs deep specialization
· Experience integrating platform management protocols (MCTP, PLDM) to enable structured telemetry, device visibility, and communication between embedded systems and host-side applications
· Exposure to embedded Linux or hybrid edge/cloud architectures
· Experience with data observability, data validation, and telemetry integrity frameworks
· Background in hardware-adjacent environments (IoT, robotics, devices)

## Description

Developing software, algorithms, and firmware for AI systems across embedded platforms (GPUs, ARM MCUs, DSPs, FPGAs)
*
Developing Edge AI software across devices using Core ML + Metal (Apple) and Android platforms
*
Deploying deterministic Edge AI pipelines on NVIDIA platforms


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