Lenovo's Advanced AI Technology Center (AAITC) is seeking to define the next era of computing powered by AI, by scaling and deploying foundation models, advancing agentic computing, and orchestrating intelligent systems.
Requirements
- Strong programming skills in Python and experience with deep learning frameworks like PyTorch.
- Solid understanding of machine learning principles, including supervised learning, unsupervised learning, and reinforcement learning.
- Proven experience in designing and conducting experiments, analyzing data, and drawing meaningful conclusions.
- Familiarity with large language models, transformer architectures, and related concepts.
- Experience with data processing tools and techniques (e.g., Pandas, NumPy).
- Experience working with Linux systems and/or HPC cluster job scheduling (e.g., Slurm, PBS).
- Experience with distributed training frameworks (e.g., DeepSpeed, Megatron-LM).
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 adversarial training techniques to improve model robustness against adversarial attacks and enhance generalization performance by exposing the model to perturbed input examples during training.
- Developing and executing SFT strategies for specific tasks.
- Running and refining RLHF pipelines to align models with human preferences.
- Design and implement model pruning strategies to reduce model size and computational complexity by removing non-essential parameters, optimizing for both performance and efficiency without significant accuracy loss.
- Develop and perform model distillation techniques to compress large language models into smaller, more efficient models while preserving key performance characteristics.
Other
- Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field and 5+ years of relevant work experience or 7+ years of relevant work experience.
- Ph.D. in Computer Science, Machine Learning, or a related field.
- Excellent communication, collaboration, and problem-solving skills.
