Startups · AI

Embedded AI Engineer

Hark · San Jose · On-site

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About Hark

At Hark, we are building the most advanced personal intelligence in the world.

About the role

As an Embedded AI Engineer, you will work closely with the AI research team to bring AI to Hark’s next-gen hardware. You will be responsible for the full AI stack on the device, including data ingestion, model development, optimization, and deployment on embedded devices.

What they're looking for

  • 5 years of experience in machine learning engineering, with at least 2 years focused on embedded or edge ML
  • Familiarity with embedded systems, and CPU/DSP/NPU HW architectures
  • Hands-on experience with IMUs and other sensor types including accelerometers, gyroscopes, and microphones
  • Experience building sensor data collection pipelines
  • Familiarity and experience with embedded ML run times (e.g. TFLite, llamacpp, QNN)
  • Experience optimizing models for deployment on microcontrollers and edge processors such as ARM Cortex-M/A, RISC-V, and DSPs
More about this role

Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory.

We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world.

To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems.

As an Embedded AI Engineer, you will work closely with the AI research team to bring AI to Hark’s next-gen hardware. You will be responsible for the full AI stack on the device, including data ingestion, model development, optimization, and deployment on embedded devices. You should have deep understanding of the constraints of an embedded system (compute, memory, power etc) and leverage your expertise in both embedded system software development and AI model deployment to...

Read the full posting on Hark's site ↗

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