Engineer, AI Model bei Lenovo

We are seeking a highly motivated and skilled Model Development Engineer to join our rapidly growing AI team in Morrisville, NC. You will play a critical role in the training of large language models (LLMs), large vision models (LVMs), and large multimodal models (LMMs), including fine-tuning and reinforcement learning. This is a challenging yet rewarding opportunity to contribute to cutting-edge research and development in generative AI. You’ll be working with a collaborative team to push the boundaries of what’s possible with AI models and deploy them into innovative products.  Responsibilities: Design, implement, and evaluate training pipelines for large generative AI models, encompassing multiple stages of post-training. Data: Design, implement, and evaluate data augmentation pipelines to increase the diversity and robustness of training datasets, improving model performance, particularly in low-data regimes. Model evaluations: Develop and implement model evaluation pipeline for LLMs Supervised Fine-tuning (SFT): Developing and executing SFT strategies for specific tasks. RLHF: Developing and leveraging RLHF algorithms in model training such as DPO and KTO Reinforcement Learning (RL): Exploring RL training strategies, sampling, reward function design and etc. to apply large scale RL to model training Quantization: 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. Low-Rank Adaptation (LoRA): Utilizing techniques for efficient fine-tuning of large language models, balancing performance and resource constraints, and tailoring model performance for downstream tasks well. Experiment with various training techniques, hyperparameters, and model architectures to optimize performance and efficiency. Develop and maintain data pipelines for processing and preparing training data. Stay up-to-date with the latest advancements in large language models, training techniques, and related technologies. Collaborate with other engineers and researchers to design, implement, and deploy AI-powered products. Contribute to the development of internal tools and infrastructure for model training and evaluation.   Qualifications: Master's degree in Computer Science, Machine Learning, or a related field and 2+ years of relevant work experience or 4+ years of relevant work experience. 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 Excellent communication, collaboration, and problem-solving skills.#LATC Jetzt bewerben