Lenovo is seeking a Model Development Engineer to contribute to cutting-edge research and development in generative AI, specifically in training large language models, large vision models, and large multimodal models.
Requirements
- Strong programming skills in Python and experience with deep learning frameworks like Pytorch, Transformers.
- Solid understanding of machine learning principles, including supervised learning, unsupervised learning, and reinforcement learning.
- Familiarity with large language models, transformer architectures, and related concepts.
- Experience with data processing tools and techniques (e.g., Pandas, NumPy).
- Experience with distributed training frameworks (e.g., DeepSpeed, Megatron-LM).
- Proven experience in designing and conducting experiments, analyzing data, and drawing meaningful conclusions.
- Ph.D degree in Computer Science, Machine Learning, or a related field.
Responsibilities
- Design, implement, and evaluate training pipelines for large generative AI models, encompassing multiple stages of post-training.
- Design, implement, and evaluate data augmentation pipelines to increase the diversity and robustness of training datasets, improving model performance, particularly in low-data regimes.
- Develop and implement model evaluation pipeline for LLMs
- Developing and executing SFT strategies for specific tasks.
- Developing and leveraging RLHF algorithms in model training such as DPO and KTO
- Exploring RL training strategies, sampling, reward function design and etc. to apply large scale RL to model training
- Implement and evaluate model quantization techniques to reduce model size and accelerate inference speed, balancing precision loss with performance gains for deployment across diverse hardware platforms.
Other
- Ph.D degree in Computer Science, Machine Learning, or a related field.
- Excellent communication, collaboration, and problem-solving skills.
- We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
- Full-time working time
- Collaborate with other engineers and researchers to design, implement, and deploy AI-powered products.
