AI Engineer – Model Optimization & Acceleration
Indexed description
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
- 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
- Edge AI or embedded deployment
- Generative or multi-modal AI systems
- Distributed inference or streaming pipelines
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
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