AI Data Intelligence Staff Researcher

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AI Data Intelligence Staff Researcher

Role Overview

Lenovo is seeking an AI Data Intelligence Staff Researcher to develop intelligent, efficient, and reliable AI solutions for Hybrid AI computing and data infrastructure.

In this role, you will use machine learning, deep learning, data science, and software engineering to improve system performance, reliability, scalability, and resource efficiency.

You will collaborate with research, engineering, and product teams to turn innovative AI research into practical solutions for Lenovo's Enterprise AI and Personal AI products.

What You'll Do

- AI/ML Research: Research and develop machine learning, deep learning, and AI solutions for computing and data infrastructure.
- Data Analysis: Analyze large datasets using statistical methods, predictive modeling, and data science techniques.
- System Optimization: Develop AI solutions to improve system performance, resource allocation, workload management, and reliability.
- Predictive Analytics: Use time-series analysis, anomaly detection, and forecasting to identify system issues and predict failures.
- Advanced AI Research: Explore reinforcement learning, causal inference, knowledge graphs, and graph neural networks.
- Software Development: Build scalable data pipelines, AI applications, APIs, and production-quality software.
- Research & Testing: Conduct experiments, evaluate model performance, and validate AI solutions.
- Collaboration: Work with research, engineering, and product teams to implement AI solutions.
- Innovation: Contribute to research publications, patents, technical reports, and reusable software.

Minimum Qualifications

- Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.
- Strong understanding of machine learning, deep learning, statistical modeling, or data science.
- Programming experience with Python, C++, or a similar language.
- Experience with AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, NumPy, or pandas.
- Knowledge of probability, statistics, linear algebra, and optimization.
- Relevant AI/ML experience through academic projects, internships, or research.
- Strong analytical, problem-solving, programming, and communication skills.

Candidates should also have knowledge or experience in at least two of the following areas:

- Machine learning or deep learning
- Statistical modeling or predictive analytics
- Time-series analysis or signal processing
- Anomaly detection or fault diagnosis
- Causal inference or optimization
- Knowledge graphs or graph machine learning
- Reinforcement learning
- Large-scale data analytics or AI systems

Preferred Qualifications

- Research or project experience in advanced machine learning, deep learning, generative AI, or reinforcement learning.
- Experience with forecasting, anomaly detection, causal inference, graph neural networks, or predictive analytics.
- Experience building scalable AI applications or production-quality software.
- Familiarity with cloud platforms, distributed computing, GPU computing, or AI infrastructure.
- Research publications, patents, open-source contributions, internships, or significant academic projects.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.