ML algorithm engineer

Key Responsibilities Develop and implement quantization of existing AI models for various fields (e.g., LLM, Vit and Dit) for our unique optical AI accelerator, enabling inference with low-bit weights and activations without compromising model accuracy. Collaborate with system engineers to deploy,analyze and enhancethe performance of quantized modelson our optical processor. Stay informed about the latest developments in model quantization, analog computing, and AI acceleration. Utilize this information to aid and informhardware design. Work closely with cross-disciplinary teams, including software developers, data scientists, and product managers, to integrate optimized AI models into comprehensive solutions. Qualification & Skills 3+ years of industry and research experience in machine learning algorithms, with a focus on model quantization techniques Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on machine learning Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch In-depth understanding of numerical representations used in machine learning and quantization techniques Experience with tools for quantization and model compression (e.g., ONNX, TVM) Excellent problem-solving skills and ability to work collaboratively across teams Strong communication skills for conveying technical insights and hardware requirements Preferred Qualifications Experience with model quantization for LLMs Experience with model quantization for analog computing. Publications or patents in AI model quantization or hardware-aware AI optimization.

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