Senior Embedded AI Engineer (Edge AI Systems Architect)

AsiaCruit, Inc.; Town of Delhi (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

Asiacruit is seeking a Senior Embedded Edge AI Systems Architect to design and optimize AI computing systems for robotics and edge applications. You will deploy AI models on embedded platforms, optimize inference, and ensure reliable operation under power and thermal constraints.

The role requires strong C++ and CUDA, experience with NVIDIA Jetson platforms (AGX Orin) and Jetson Linux, ROS 2 integration, and sensor synchronization.

Qualifications

• Degree in a relevant engineering or CS field; advanced degree preferred.
• 5+ years in embedded systems with hands-on edge AI experience.
• Proven track record deploying AI on NVIDIA Jetson platforms.
• Strong C++ and CUDA programming skills; Linux experience.

Responsibilities

• Design embedded AI computing architectures for robotics and edge devices.
• Optimize AI inference performance using CUDA, TensorRT, and model quantization.
• Deploy quantized models on embedded hardware and integrate sensors.
• Develop high-performance IPC and data pipelines; ROS 2 integration.
• Collaborate with AI, robotics, and hardware teams to validate on real platforms.

Skills

C++

CUDA programming

Embedded systems

ROS 2

TensorRT

Education

Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or related field

Master's degree in related field (preferred)

Tools

NVIDIA Jetson

NVIDIA Jetson Linux (L4T)

TensorRT-LLM

CUDA

ROS 2

Job description

About Asiacruit

At Asiacruit, we connect top talent with forward-thinking organizations across industries. Our mission is to help businesses grow through smart, strategic, and people-focused solutions. We support companies by providing high-quality talent for local and global markets.

At Asiacruit, we connect top talent with forward-thinking organizations across industries. Our mission is to help businesses grow through smart, strategic, and people-focused solutions. We support companies by providing high-quality talent for local and global markets.

Position Overview

We are looking for a Senior Embedded Edge AI Systems Architect to design and optimize AI computing systems for advanced robotics and edge applications.

In this role, you will deploy AI models on embedded computing platforms, optimize inference performance, integrate sensors and software systems, and ensure reliable operation under hardware, power, and thermal constraints.

Key Responsibilities

• Design embedded AI computing architectures using NVIDIA Jetson platforms, including Jetson AGX Orin.
• Optimize AI inference performance using CUDA, TensorRT, TensorRT-LLM, and model quantization techniques.
• Deploy quantized neural network models on embedded and robotic hardware.
• Develop high-performance communication pipelines between AI inference systems and robotics middleware, including ROS 2.
• Implement zero-copy data transfer and shared-memory inter-process communication.
• Integrate and synchronize data from 3D LiDAR, RGB-D cameras, stereo cameras, and IMUs.
• Implement sensor synchronization using IEEE 1588 Precision Time Protocol (PTP) and hardware timestamping.
• Optimize system power consumption, thermal performance, and computing efficiency.
• Implement hardware watchdogs and reliability mechanisms for embedded systems.
• Collaborate with AI, robotics, and hardware engineering teams to validate system performance on physical platforms.

Qualifications

• Bachelor's or Master's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
• At least 5 years of embedded systems experience, with substantial hands‑on experience in embedded AI or edge computing.
• Proven experience deploying AI models on NVIDIA Jetson platforms or comparable embedded AI hardware.
• Strong proficiency in C++ and CUDA programming.
• Hands‑on experience with embedded Linux and NVIDIA Jetson Linux (L4T).
• Experience optimizing AI inference using TensorRT. TensorRT-LLM experience is highly relevant.
• Understanding of neural network quantization techniques, including INT8, INT4, or FP8.
• Experience with shared memory, zero-copy data pipelines, or high-performance inter-process communication.
• Knowledge of ROS 2 integration and real‑time sensor data processing.
• Familiarity with IEEE 1588 PTP, hardware timestamping, and sensor synchronization.
• Understanding of embedded hardware power management, thermal optimization, and system reliability.

Why Join?

• Work on advanced AI and robotics engineering challenges.
• Contribute to deploying AI models on real-world embedded computing platforms.
• Collaborate with multidisciplinary teams across AI software, robotics, and hardware engineering.
• Take ownership of system architecture, performance optimization, and hardware integration.