Embedded Systems Engineer, -Device Inference

Embedded Systems Engineer, On-Device Inference

You will bring the addressee-detection model on-device, building efficient inference for regulated and OEM hardware where a GPU is not an option. This is the work that lets our models run where the audio actually happens.

• Take our models from the server to the device, running efficiently on constrained CPUs.
• Optimize inference with tools like ONNX, quantization, and careful profiling, without a GPU to lean on.
• Work close to the metal on audio pipelines, memory, and latency budgets.
• Partner with research and OEM customers to fit the model to real hardware and real constraints.
• Build the tooling and tests that keep on-device behavior honest across devices.

What we are looking for

• Strong systems and embedded experience: C or C++, plus comfort in Python for tooling.
• A track record of making models or signal code run fast on constrained hardware.
• Familiarity with inference runtimes, quantization, and profiling for CPU targets.
• Care for correctness and reliability in environments you cannot easily update.
• Comfort owning a hard, specific problem end to end.
• Bonus: experience with audio DSP, real time constraints, or shipping software into physical devices.

About attention labs

attention labs is early: a small team defining a new category at the intersection of speech, cognitive neuroscience, and machine learning. We work from San Francisco, Toronto, and Memphis, and we are remote-friendly for the right person.