SDE II - Gen AI New

NetVerks Inc.; India; On-site; INR 1,500,000 - 3,000,000; Full time

Job summary

Glance is seeking an engineer to advance generative AI on mobile and TV devices. You will work across PyTorch, Python, and CV models, focusing on LoRA fine-tuning, model optimization, and efficient on-device deployment.

You’ll build training pipelines, experiment with diffusion and transformer architectures, and optimize inference with ONNX, TensorRT, Core ML, and TFLite/LiteRT while reducing latency and memory footprint.

Qualifications

• 2–5 years of experience in deep learning or CV.
• Hands-on experience with image-generation models.
• Good understanding of LoRA, optimization and quantization.
• Experience with inference runtimes (ONNX, TensorRT, Core ML, TFLite).

Responsibilities

• Image generation for identity-preserving and reference-based outputs.
• LoRA training, fine-tuning, personalization, and adapters.
• PyTorch-based training and experimentation.
• Diffusion/Transformer image generation architectures.
• Dataset prep, training pipelines and evaluation.
• Model conversion and deployment with ONNX / ONNX Runtime.
• Inference optimization with TensorRT.
• Quantization (FP16/INT8/INT4) and other optimizations.
• On-device inference for iOS (Core ML) and Android (TFLite/LiteRT).
• Profiling and debugging across CPU, GPU, NPU/ANE.
• Reduce latency, memory usage, and model footprint.
• Build end-to-end pipelines from training to device deployment.

Skills

Python

PyTorch

Deep learning

Computer Vision

LoRA fine-tuning

Model optimization

Quantization

On-device deployment

Debugging & profiling

Tools

ONNX Runtime

TensorRT

Core ML

TFLite/LiteRT

Job description

Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV - shaping the new era...

Glance Glance is an intelligent shopping agent, redefining the commerce experience. Powered by proprietary agentic intelligence and generative AI, Glance delivers a hyper-personalized consumer experience across mobile and TV - shaping the new era of shopping. Glance is operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of global technology leader InMobi, and is backed by Mithril Capital, Google and Jio Platforms. To learn more, visit glance.com. InMobi InMobi Group is a global technology company shaping the future of agentic commerce and advertising. Through its ecosystem of businesses - including InMobi Advertising and flagship consumer platform Glance - InMobi leverages data, machine learning, and generative AI to help brands reach audiences more precisely and consumers discover products more intuitively. Glance, which is pioneering new models of agentic commerce, is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. InMobi Advertising InMobi Advertising, part of global technology company InMobi, is an agentic advertising platform helping brands and merchants achieve their business outcomes. Through its proprietary intelligence, AI-led solutions, and vast consumer reach - including flagship consumer platform Glance - InMobi Advertising delivers the omnichannel performance defining what's next in advertising and commerce. Glance is owned and operated by Glance InMobi Pte. Ltd., a non-consolidated subsidiary of InMobi Pte. Ltd. To learn more, visit advertising.inmobi.com. We’re looking for an engineer who can work across Generative AI, model fine-tuning, optimization, and on-device deployment for iOS and Android. This role is ideal for someone who enjoys taking models beyond experimentation and making them actually work on consumer devices under real constraints such as latency, memory, battery, thermal limits, and model size.

What you’ll work on

• Image Generation, VTON, identity-preserving and reference-based generation
• LoRA training, fine-tuning, personalization, and adapter-based techniques
• PyTorch-based training and experimentation
• Diffusion / Transformer-based image generation architectures
• Dataset preparation, training pipelines, and evaluation
• Model conversion and deployment using ONNX / ONNX Runtime
• Inference optimization using TensorRT
• Quantization using FP16 / INT8 / INT4 and other optimization techniques
• On-device inference on iOS using Core ML and Android using TFLite/LiteRT, ONNX Runtime, or similar runtimes
• Performance profiling and debugging across CPU, GPU, NPU / ANE
• Reducing inference latency, peak memory usage, and model footprint
• Building production-ready model pipelines from training to device deployment

What we’re looking for

• 2-5 Years of Experience
• Strong experience with Python, PyTorch, and deep learning
• Hands-on experience with Computer Vision / Generative AI
• Experience training or fine-tuning image-generation models
• Good understanding of LoRA, model optimization, and quantization
• Strong knowledge of inference runtimes such as ONNX, TensorRT, Core ML, TFLite/LiteRT, or ONNX Runtime
• Strong debugging, profiling, and software engineering fundamentals

Good to have

• Experience with FLUX, Stable Diffusion, SDXL, ControlNet, IP-Adapter, VAE, CLIP, or similar architectures
• CUDA / GPU optimization
• Metal / Apple Neural Engine
• Android NNAPI / GPU delegates
• C++ / Swift / Kotlin
• Distributed or multi-GPU training
• Model compression, pruning, and knowledge distillation

We’re especially interested in engineers who can think end-to-end: Data Training Fine-tuning Evaluation Quantization Model Conversion Runtime Optimization On-Device Deployment Production Monitoring

If you enjoy solving problems like "How do we make a large generative model run fast, efficiently, and reliably on a phone?", this role should be exciting.

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