Model Data Engineer

We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world's largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo's continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

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.