Edge AI Engineer – On-Device GenAI & Embedded ML

Nutanix; San Diego (CA); On-site; USD 123,000 - 184,000; Full time

Job summary

Qualcomm AI Research is seeking talented AI software engineers to enable AI technologies on edge devices. Join a high-caliber team building GenAI solutions with optimized models for power, memory, and computation on Qualcomm hardware.

You will work across hardware, software, and systems to deploy state-of-the-art models on embedded chips in devices like smartphones, robots, and IoT. The role involves developing end-to-end embedded AI software, enhancing ML/AI software stacks, and collaborating

Qualifications

• Bachelor's degree in CS/engineering/IS or related field.
• 1 year of work experience preferred.
• Proficient in C/C++ and Python.
• Experience with deep learning frameworks like PyTorch.
• Knowledge of Android programming is a plus.
• Experience with Qualcomm QNN SDK is a plus.

Responsibilities

• Develop end-to-end embedded AI software to train and finetune neural networks on Qualcomm hardware with optimum resources.
• Design and enhance ML/AI software stack, kernels, and runtime for performance and power efficiency.
• Collaborate with AI Processor Hardware team to implement ML operators/layers that utilize next-gen AI processor capabilities.
• Develop debugging/profiling tools and user-friendly SDKs to enable rapid deployment of use cases.

Skills

C/C++

Python

Software debugging

Android programming

Education

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

Tools

PyTorch

QNN SDK

Job description

Qualcomm AI Research is seeking talented AI software engineers to enable AI technologies on edge devices. Join a high-caliber team building GenAI solutions with optimized models for power, memory, and computation on Qualcomm hardware.

You will work across hardware, software, and systems to deploy state-of-the-art models on embedded chips in devices like smartphones, robots, and IoT. The role involves developing end-to-end embedded AI software, enhancing ML/AI software stacks, and collaborating