Job Description
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