AI Data Intelligence Researcher

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AI Data Intelligence Staff Researcher

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.

• 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.

• 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, Tensor Flow, scikit-learn, Num Py, 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.

• 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
• Lar…