SDE II - Gen Ai

GlanceGlance 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 AdvertisingInMobi 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 onImage Generation, VTON, identity-preserving and reference-based generationLoRA training, fine-tuning, personalization, and adapter-based techniquesPyTorch-based training and experimentationDiffusion / Transformer-based image generation architecturesDataset preparation, training pipelines, and evaluationModel conversion and deployment using ONNX / ONNX RuntimeInference optimization using TensorRTQuantization using FP16 / INT8 / INT4 and other optimization techniquesOn-device inference on iOS using Core ML and Android using TFLite/LiteRT, ONNX Runtime, or similar runtimesPerformance profiling and debugging across CPU, GPU, NPU / ANEReducing inference latency, peak memory usage, and model footprintBuilding production-ready model pipelines from training to device deploymentWhat we’re looking for2-5 Years of ExperienceStrong experience with Python, PyTorch, and deep learningHands-on experience with Computer Vision / Generative AIExperience training or fine-tuning image-generation modelsGood understanding of LoRA, model optimization, and quantizationStrong knowledge of inference runtimes such as ONNX, TensorRT, Core ML, TFLite/LiteRT, or ONNX RuntimeStrong debugging, profiling, and software engineering fundamentalsGood to haveExperience with FLUX, Stable Diffusion, SDXL, ControlNet, IP-Adapter, VAE, CLIP, or similar architecturesCUDA / GPU optimizationMetal / Apple Neural EngineAndroid NNAPI / GPU delegatesC++ / Swift / KotlinDistributed or multi-GPU trainingModel compression, pruning, and knowledge distillationWe’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 MonitoringIf 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.