Why Work at Lenovo

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

Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 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).

• Collaborate with stakeholders to understand business requirements and identify opportunities for applying AI technologies.
• Research, design, and develop machine learning models and algorithms to solve specific business problems.
• Collect, preprocess, and analyze large datasets to extract meaningful insights and patterns.
• Implement and optimize AI models for performance, scalability, and reliability.
• Integrate AI solutions into existing systems and workflows, ensuring seamless operation and compatibility.
• Evaluate and test AI models to ensure accuracy, robustness, and effectiveness in real-world scenarios.
• Stay updated on the latest advancements in AI technologies, tools, and techniques, and propose innovative ideas for leveraging AI in Manufacturing and/or Supply Chain
• Collaborate with cross-functional teams, including data scientists, engineers, product managers, and business stakeholders, to drive AI initiatives from concept to production.

• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field.
• Proven experience in developing and deploying AI solutions in real-world applications.
• Strong programming skills in languages such as Python, R, or Java, with experience in libraries/frameworks like TensorFlow, PyTorch, or scikit-learn.
• Solid understanding of machine learning techniques, algorithms, and methodologies.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Proficiency in data visualization and exploratory data analysis.
• Excellent problem-solving skills and attention to detail.
• Strong communication and interpersonal skills, with the ability to collaborate effectively in a team environment.
• English Profiency