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), CPU,NPU,GPU,AI,multi-modal,speech,LLMS,PyTorch,ONNX,runtimes,GNU,NPU,FP32,debug,lower precision
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
Robust 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

Experience

710 years
Role & responsibilities

Preferred candidate profile

Perks and advantages

📌 Ai Engineer Model Optimization & Acceleration Bangalore Rural
🏢 Sunrise BizTech Systems
📍 Bangalore Rural