Job Description

About Reliance Intelligence

Reliance Intelligence is a Reliance Industries subsidiary building India's most advanced AI-powered consumer devices. Our flagship product, JioFrames AI, is India's first AI-powered smart eyewear — combining on-device machine learning, AR overlays, real-time translation, health monitoring, and the JioAI assistant in a sleek wearable form factor. Backed by the JioEcosystem with 450M+ users and unmatched distribution reach, we are building at the intersection of hardware, AI, and consumer experience.

Roles & Responsibilities

Build and deploy on-device ML models for JioFrames AI features — object detection, scene understanding, gesture recognition, OCR, and health sensing
Optimize models for wearable SoC deployment using quantization (INT8/INT4), pruning, and knowledge distillation within strict power and memory budgets
Develop and maintain real-time inference pipelines handling camera frames, microphone input, and sensor fusion on constrained hardware
Build and fine-tune NLP models for intent recognition, wake-word detection, and command parsing running locally on JioFrames AI
Integrate LLM capabilities for the JioAI assistant — enabling natural conversation, live translation, and contextual Q&A
Establish ML training pipelines, experiment tracking, and model versioning using MLflow or equivalent
Design and implement OTA model update mechanisms to continuously improve AI capabilities post launch
Collaborate closely with firmware, hardware, and Android teams to ship AI features end-to-end

Requirements

4–10 years of hands-on ML/AI engineering experience with production deployments
Strong proficiency in PyTorch or TensorFlow and on-device inference runtimes — TFLite, ONNX Runtime, or QNN SDK
Proven experience in model optimization for edge deployment — quantization, pruning, and latency profiling
Solid background in computer vision — object detection, classification, OCR, or depth estimation
Experience with NLP or multimodal AI; familiarity with LLM fine-tuning or RAG pipelines is a plus
Comfortable working close to hardware — NPU/DSP pipelines, camera ISP, and wearable power constraints
Strong Python skills; C/C++ and experience with Qualcomm Hexagon SDK is advantageous
Experience shipping AI features on mobile, wearables, IoT, or embedded platforms preferred