AI model optimization & acceleration Engineer

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

Good to Have

• Edge AI or embedded deployment

• Generative or multi-modal AI systems

• Distributed inference or streaming pipelines