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. 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. Solid 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.

📌 Senior Embedded AI Engineer (Edge AI SystemsArchitect) (New Delhi)
🏢 Asiacruit BPO
📍 New Delhi