Autonomous Driving Software Engineer
6 - 10 years
Lehi, UT
$150k - $175k/year
Full-time
Hybrid
1 month ago
About the role
Embedded Software Engineer IV – AI Applications
Salt Lake City Region (hybrid/onsite)
Target Start Date : ASAP
Contract-to-Hire (Direct Hire possible)
Pay Rate: $70.00-$85.00/hr ($150-$175K)
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
Requirements
Salt Lake City Region (hybrid/onsite)
Target Start Date : ASAP
Contract-to-Hire (Direct Hire possible)
Pay Rate: $70.00-$85.00/hr ($150-$175K)
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.