
Optimizing Large Models
5 days ago
We are seeking a skilled Large Model Optimization Engineer to join our team. In this role, you will be responsible for developing and optimizing large models for inference and training.
Your primary focus will be on designing and optimizing self-developed NPU software and hardware systems to achieve high-performance compilation. You will also collaborate closely with the chip department for hardware-software optimization and research cutting-edge technologies for large models.
The ideal candidate will possess a Master's or Bachelor's degree in Computer Science, Electronics, Automation, Software, or related fields and have proficient knowledge of algorithms and data structures. Strong experience with high-performance computing optimization techniques, distributed parallel computing optimization, memory access optimization, and low-bit computation is essential. Familiarity with deep learning algorithms, neural network architectures, operator computation methods, and frameworks like PyTorch, TensorFlow, or MindSpore is highly valued.
Responsibilities- Developing large model operators and optimizing parallel strategies for inference and training.
- Designing and optimizing self-developed NPU software and hardware systems for high-performance compilation.
- Collaborating with the chip department for hardware-software optimization.
- Researching and introducing cutting-edge technologies for large models.
- Master's or Bachelor's degree in Computer Science, Electronics, Automation, Software, or related fields.
- Proficient knowledge of algorithms and data structures.
- Strong experience with high-performance computing optimization techniques.
- Familiarity with deep learning algorithms and neural network architectures.
- Experience with frameworks like PyTorch, TensorFlow, or MindSpore.
- A culture valuing authenticity and diversity of thoughts and backgrounds.
- An inclusive environment with open workspaces and a start-up spirit.
- Opportunities to network with industry pioneers and enthusiasts.
- Contributing directly to the future of the digital asset industry.
- Involvement in new projects and developing processes/systems.
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