Principal Edge AI Firmware Engineer (C/C++)

Location: Austin, Texas, United States. Must be currently authorized to work in the United States for any employer.

Company

hirify.global develops ultra-low-power semiconductor solutions for wearables, medical devices, IoT products, and AI-powered edge applications.

What you will do

• Develop and support embedded AI runtimes, including HeliaRT and HeliaAOT, with a focus on portability, correctness, performance, and usability.
• Implement and optimize ML operator kernels and embedded libraries for DSP, vector, and NPU acceleration.
• Build on-device profiling, performance analysis, benchmark, microbenchmark, and regression-testing tools.
• Improve latency, memory footprint, bandwidth usage, and energy efficiency through compute and memory-hierarchy analysis.
• Enable customer integration across bare-metal, FreeRTOS, Zephyr, Arm toolchains, and embedded build systems.
• Improve runtime memory planning, maintain upstream and fork health, and publish documentation, examples, and benchmarks.

Requirements

• BS in Electrical or Computer Engineering, Computer Science, or a related field, plus 12+ years of relevant experience, or equivalent practical experience.
• Strong experience designing, developing, and testing embedded software in C/C++.
• Strong debugging discipline focused on correctness, reproducibility, and preventing performance regressions.
• Understanding of compute, memory, bandwidth, cache effects, deterministic latency, and energy efficiency in constrained systems.
• Experience interpreting hardware and software documentation, using Git, and working with Arm toolchains, GDB, J-Link or SEGGER-class probes, and CMake or Make.
• Current authorization to work in the United States for any employer is required.

Nice to have

• Python for profiling, analysis, automation, and developer utilities.
• Rust experience and familiarity with TensorFlow Lite for Microcontrollers or similar embedded inference runtimes.
• Experience with DSP, vector, or NPU optimization; CMSIS-NN, CMSIS-DSP, or Vela.
• Knowledge of quantized inference, packaging and integration, or lab-based power and debugging measurements.

Culture & Benefits

• Cross-functional collaboration across platform, silicon, applied ML, and customer-facing teams.
• Work on energy-efficient semiconductor technology for real-world edge AI applications.
• Values include innovation, collaboration, focus, learning, and achievement.
• Opportunity to work on complex embedded systems and meaningful technical challenges.