Job Title: AI Engineer – Model Optimization & Acceleration
Location: Bangalore, India
Role Overview
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.
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
Solid 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
Good to Have
Edge AI or embedded deployment
Generative or multi-modal AI systems
Distributed inference or streaming pipelines