Embedded Machine Learning Engineer
Location
Seattle, WA
Level
Mid-Level
Department
Consumer Electronics
Type
Salary
$140,000 - $260,000
Job Description
Posted on:
2026-01-16
Responsibilities
- Design and implement efficient ML inference pipelines on resource-constrained embedded hardware.
- Optimize neural network models for performance, memory, and power on edge devices.
- Develop and integrate robust C/C++ software for deploying ML models on microcontrollers, DSPs, and ML accelerators.
- Analyze and debug performance bottlenecks and power consumption across the hardware/software stack for ML workloads.
- Collaborate with ML researchers, hardware engineers, and platform teams to deliver high-quality, power-efficient edge AI solutions.
- Evaluate and recommend embedded platforms, toolchains, and ML frameworks for on-device intelligence applications.
Job Requirements
- Bachelor’s degree (3+ years experience) or Master’s degree (2+ years experience) in CS, EE, or a related technical field.
- Proficiency in C/C++ for embedded systems development, including RTOS and microcontrollers.
- Proven ability to optimize and deploy ML models for resource-constrained edge devices.
- Strong analytical and debugging skills to resolve performance bottlenecks across hardware, firmware, and ML inference.
- Experience with ML inference hardware acceleration and familiarity with neural network architectures.
- Knowledge of computer vision, NLP, or audio processing in an embedded/robotics context.
- Experience with embedded Linux or other RTOS in a production environment.
