Generative AI Models Optimization

Job Title: Generative AI Models Optimization Engineer - NPU Hardware

Job Description:

Overview:
We are seeking a skilled and innovative Generative AI Models Optimization Engineer to join our dynamic team. In this role, you will be responsible for developing and optimizing generative AI models specifically tailored for Neural Processing Unit (NPU) hardware. As a key member of our AI research and development team, you will play a crucial role in advancing the efficiency and performance of our cutting-edge AI applications.

Responsibilities:

Generative AI Model Development:

Design, implement, and optimize generative AI models for deployment on NPU hardware.
Collaborate with cross-functional teams to understand application requirements and tailor models for specific use cases.
NPU Hardware Optimization:

Analyze and profile NPU hardware architecture to identify optimization opportunities.
Implement and fine-tune algorithms to maximize performance and minimize resource utilization on NPUs.
Performance Evaluation:

Conduct rigorous testing and performance evaluations to ensure generative AI models meet quality standards and deliver optimal results on NPU hardware.
Collaborate with QA teams to establish benchmarking criteria and validate model performance across various scenarios.
Algorithmic Efficiency:

Work on enhancing algorithmic efficiency to ensure that generative AI models are capable of real-time generation while maintaining high-quality outputs.
Implement and experiment with state-of-the-art techniques for model compression and quantization.
Collaboration:

Collaborate with hardware engineers, software developers, and researchers to integrate optimized models into end-to-end AI systems.
Provide technical expertise and guidance to cross-functional teams.
Documentation:

Document optimization methodologies, best practices, and performance results.
Create clear and comprehensive documentation for both technical and non-technical stakeholders.
Qualifications:

Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field.
Proven experience in developing and optimizing generative AI models.
Solid understanding of Neural Processing Unit (NPU) architecture and hardware constraints.
Proficiency in programming languages such as Python, TensorFlow, PyTorch, or C++.
Experience with model compression, quantization, and other optimization techniques.
Strong problem-solving skills and the ability to work in a collaborative team environment.
Preferred Skills:

Familiarity with deep learning frameworks and libraries.
Knowledge of hardware acceleration technologies and frameworks.
Experience with parallel computing and distributed systems.
Previous work on AI applications in computer vision, natural language processing, or speech recognition is a plus.
If you are passionate about pushing the boundaries of AI optimization on NPU hardware and want to be part of a team driving innovation, we encourage you to apply. Join us in shaping the future of generative AI applications.