Machine Learning Intern

Machine Learning Engineer – Edge AI & Computer Vision

Company:

InfiVR Location:

On-site Employment Type:

Internship

About InfiVR

InfiVR builds advanced VR/AR and AI-powered enterprise solutions. We specialize in real-time, on-device intelligence for immersive training, industrial automation, and smart assistance systems.

We are hiring a Machine Learning Engineer with strong expertise in

Edge AI, small LLMs, and Computer Vision , capable of building optimized models that run efficiently on AR glasses, mobile devices, and embedded systems.

Role Overview

You will design, train, optimize, and deploy machine learning models for

on-device inference

with strict latency and memory constraints.

Your focus areas:

Small LLMs / SLMs ( Computer Vision models for real-time applications Model compression & quantization Edge deployment & performance optimization with tools like Qualcomm AI hub

Key Responsibilities

Train and fine-tune

small LLMs

for domain-specific applications. Use of tools like Qualcomm AI Hub. Develop and optimize small Computer Vision models for image explanation and description like smolvlm. Apply quantization, pruning, distillation, LoRA/QLoRA. Deploy models using TensorFlow Lite, ONNX Runtime, TensorRT, or PyTorch Mobile. Optimize models for low-latency, low-memory environments. Build real-time AI pipelines for AR/VR and Android-based devices. Work closely with Unity, mobile, Android native module, and backend teams for AI integration.

Required Skills

Strong Python, PyTorch and/or TensorFlow expertise. Hands-on experience with offline edge deployment and model optimization. Experience with YOLO, MobileNet, EfficientNet or similar lightweight architectures. Knowledge of transformer architectures and small LLM fine-tuning. Experience deploying models on Android, embedded systems, or edge hardware. Strong understanding of memory, compute, and inference optimization.

What We’re Looking For

Someone who has deployed real on-device AI systems (not cloud training). Strong performance optimization mindset. Comfortable working in R&D-driven, fast-moving environments.