Hark logo
Hark Verified
Industrial IoT

Embedded AI Engineer

San Jose, CAOnsiteFull Time$200,000–$450,000 /yrPosted 2 months ago

Is this role right for you?

Upload your resume and get a skill-by-skill breakdown — see exactly where you match, where you're close, and what to highlight. Not a mystery percentage.

Get a tailored resume highlighting what this role needs.

Required skills

  • Embedded AI
  • Next-gen hardware
  • AI research
  • Embedded system constraints
  • Compute
  • Memory
  • Power
  • Bandwidth
  • Production-ready ML solutions
  • Sensor data collection pipelines

Nice to have

  • Audio models
  • Voice models
  • Vision models
  • Wearables
  • Robotics
  • Industrial sensing

Role summary

Hark is seeking an Embedded AI Engineer to integrate AI into next-generation hardware. This role involves managing the full AI stack on-device, from data ingestion and model development to optimization and deployment. The ideal candidate will have a strong understanding of embedded system constraints and expertise in both embedded software development and AI model deployment to deliver production-ready ML solutions. Responsibilities include building data pipelines, co-designing models with AI research, optimizing for hardware, and evaluating silicon platforms.

About Hark

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.

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. 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 deliver production-ready ML solutions on hardware

Responsibilities

  • Build data collection and ingestion pipelines for an embedded system including various sensors, at scale
  • Work closely with model teams to co-design model architectures that meets the required latency, memory, power, and bandwidth
  • Work with platform vendors to bring up toolchains, SDKs and new accelerator to ensure efficient model deployment and optimization
  • Integrate ML inference into embedded firmware written in C, C++, or Rust
  • Profile and optimize memory usage, power consumption, and real-time performance
  • Evaluate and select silicon platforms (GPUs, NPUs etc.) for Hark’s next gen on-device and edge deployment of a wide range of models
  • Requirements

  • 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
  • Experience deploying workloads on NPUs or specialized accelerators for embedded systems
  • Bonus Qualifications

  • Experience with Audio/Voice/Vision models
  • Experience with light weight LLM models
  • Understand the performance characteristics of edge AI models, including CNN, RNN, transformers, KV-cache behavior, and their memory bandwidth requirements.
  • Experience designing hybrid edge-LLM pipelines or integrating small language models on device
  • Prior work on products in wearables, robotics, industrial sensing, or IoT
  • Compensation

    The US base salary range for this full-time position is between $200,000 - $450,000 annually.

    The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

    Ready to apply?
    You'll be redirected to Hark's application page.

    Similar roles

    See how RiseMe works

    Match, tailor, and prep so you send fewer applications and land more interviews.