Senior Embedded AI Engineer for Autonomous Systems

ConsultNet Technology Services and Solutions; Lehi (UT); On-site; Full time

Job description

Embedded Software Engineer IV – AI Applications

Salt Lake City Region (hybrid/onsite)

Target Start Date: ASAP

Overview

Our client, a leader and growing presence in the robotics and autonomous vehicles space, is seeking a senior Embedded Software Engineer to deploy and optimize AI capabilities on constrained, real-time hardware platforms supporting autonomous robotic systems. This role focuses on embedded performance, efficient compute and memory utilization, and reliable real-time operation, bridging AI model development and production‑grade embedded deployment.

Responsibilities

• Deploy and optimize AI/ML models on embedded and constrained hardware platforms.
• Tune compute, memory, latency, and power consumption for real‑time embedded operation.
• Convert trained AI models into production‑ready embedded libraries or hardware‑optimized modules.
• Integrate embedded AI components with robotics, firmware, and system software.
• Optimize AI inference pipelines using hardware accelerators and ML runtimes.
• Validate and monitor AI performance on embedded platforms to ensure robustness and stability.
• Collaborate with cross‑functional AI, robotics, and software teams across research and product environments.
• Continuously improve embedded AI systems through performance analysis, optimization, and updates.

Requirements

• Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
• 10+ years of embedded software engineering experience, including 2–5+ years deploying AI/ML on embedded systems.
• Expert‑level programming experience with C/C++ for embedded and real‑time systems.
• Experience with RTOS and multithreaded embedded applications.
• Hands‑on experience deploying ML inference using TensorRT, ONNX Runtime, OpenVINO, or TensorFlow Lite.
• Strong understanding of embedded Linux, microcontrollers, and hardware accelerators.
• Proven ability to optimize performance, memory, and power usage in constrained environments.
• Strong analytical skills and ability to deliver reliable, production‑grade embedded AI solutions.