Model Data Engineer at Lenovo

We are seeking a highly motivated and skilled Model Data 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:  Data pipeline: Develop and implement data pipelines to build high quality training data for Large Language Model. Build Data management and DVC systems. Data Types: SFT, DPO, and RL data implementation, distillation and filtering, with data domains in general chat, instruction following, agentic tool-calling and so on. Data Quality & Evaluation: Perform thorough data analysis to assess data quality, identify anomalies, and ensure data integrity. Utilize machine learning tools and techniques to evaluate dataset performance and identify areas for improvement. Model Evaluation: Help build model evaluation framework, conduct evaluations on LLM, Multimodal LLM, Reasoning Models and etc.  Domain Model evaluation and Data: Create domain dataset and  evaluate model domain capabilities. Work closely with researchers and cross functional teams to build SOTA models together. Stay up-to-date with the latest advancements in large language models. Collaborate with other engineers and researchers to design, implement, and deploy AI-powered products.  Contribute to the development of internal tools.  Qualifications:  Master's degree in Computer Science, Machine Learning, Data Science or a related field and 2+ years of relevant work experience or 4+ years of relevant work experience.  Strong programming skills in Python and SQL  Solid understanding of data structure,  relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra). Proven experience in designing and conducting experiments, analyzing data, and drawing meaningful conclusions.  Solid understanding of machine learning concepts and techniques, including data preprocessing, feature engineering, and model evaluation. Experience with model evaluation frameworks such as Open-compass.  Familiarity with large language models, transformer architectures, and related concepts.  Excellent communication, collaboration, and problem-solving skills. #LATC Apply Now