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Edge AI Engineer

Deploy vision and perception models to edge hardware for an Australian IoT scale-up.

Sydney, Australia · HybridPermanentAUD 145k–195k
Representative role.This is a composite of searches we run regularly at this level and stack. If your background matches, apply anyway — we’ll match you to similar live briefs.

An Australian IoT company is shipping edge-AI inference on its product line. This role sits between the ML team (who train the models) and the product-firmware team (who ship the product) — your job is making the handoff work.

You'll be working primarily with Jetson Orin Nano and Hailo-8L class hardware, deploying vision and time-series models, and keeping the pipeline from model-train to fleet-rollout sharp.

What you’ll do

  • Take trained models and make them run efficiently on Jetson / Hailo / Coral — quantisation, TensorRT, tooling
  • Build the deployment pipeline: OTA firmware + model bundle + rollback
  • Profile inference and optimise — latency, thermal, power
  • Write the fleet-level monitoring that tells us when an edge device's inference quality degrades

What you bring

  • 3+ years on embedded / edge ML deployments
  • Hands-on with at least one edge-AI accelerator (Jetson, Hailo, Coral, Qualcomm AI Engine)
  • Python + C/C++; comfortable with ONNX, TensorRT, or TFLite Micro
  • Linux on embedded; device tree basics; cross-compilation

Nice-to-haves

  • Experience with Foxglove or other edge-fleet tooling
  • Model quantisation-aware training experience
  • Prior role at an edge-AI or robotics company

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