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

- 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

Experience 710 years

- Role & responsibilities

Preferred candidate profile

Perks and benefits

📌 AI Engineer Model Optimization & Acceleration (Bangalore Rural)
🏢 Sunrise BizTech Systems
📍 Bangalore Rural