Project Details AI model optimization & acceleration Job Description Seeking an AI Engineer to optimize and deploy ML models across heterogeneous platforms (CPU, GPU, NPU). Work on scalable, production-ready AI systems across domains like robotics, healthcare, and automotive. Experience : 4-10 Years Job Responsibilities / Day-to-Day Activities Qualifications & Experiences: Key Responsibilities • Optimize diverse models: generative (LLMs, diffusion), vision (classification, detection, segmentation), multi-modal, and speech • Port models across frameworks (e.g., PyTorch → ONNX → runtimes) • Deploy on hardware accelerators (GPU/NPU) and optimize performance • Improve inference latency, throughput, and memory (batching, caching, parallelism, fusion)



• Apply quantization and model compression (FP32 → lower precision) • Profile and debug system and model performance Required Skills • Strong in PyTorch (or similar), ONNX (or equivalent) • Proficient in Python and C++ • Experience with GPU/hardware acceleration (CUDA/ROCm or similar) • Solid understanding of deep learning models (transformers, CNNs) • Knowledge of optimization, quantization, and performance tuning Valuable to Have • Edge AI or embedded deployment • Generative or multi-modal AI systems • Distributed inference or streaming pipelines

📌 AI model optimization (Karnataka)
🏢 L&T Technology Services
📍 Karnataka