Time Series Data Analysis Based on Large Language Model
il y a 3 semaines
Time Series Data Analysis Based on Large Language Model (LLM) Engineer - Paris, France
Location: Paris
Job Description: We are looking for a talented software engineer to lead innovative projects focused on the application of large language models (LLMs) like BERT and GPT in time series data analysis. This role involves research and development in areas such as time series forecasting, classification, and anomaly detection using LLMs.
For this position, the focus will be on hands-on engineering and coding rather than theoretical research or academic paper writing.
Key Responsibilities:
Research and Development:
- Investigate the feasibility of applying LLMs to time series tasks like forecasting, anomaly detection, and classification.
- Design and implement novel models to enhance LLM performance in time series applications.
- Explore and identify use cases for time series models across different industries, such as data communication.
Model Development and Optimization:
- Adapt and fine-tune LLMs to effectively handle time series data.
- Lead model training, fine-tuning, and optimization for large-scale time series datasets.
Data Analysis and Applications:
- Work with time series databases (TSDB) to clean, process, and model data.
- Develop methods for time series data mining, integrating LLMs to improve decision-making processes.
Cross-team Collaboration:
- Collaborate with the TSDB team to bring research results into practical, real-world applications.
Qualifications:
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Data Science, Statistics, or related fields.
- Strong foundation and practical experience in natural language processing (NLP), machine learning, and deep learning.
- Familiarity with LLMs like GPT and BERT, with hands-on experience in research or development.
- Deep understanding of time series data and applications, including forecasting, classification, and anomaly detection. Knowledge of TSDB technologies is a plus.
- Proficiency in Python, PyTorch, and related tools, with strong algorithm design skills.
- Independent research abilities in frontier areas of AI.
Preferred Qualifications:
- Published research papers in top-tier conferences or journals.
- Experience in time series data applications in industries like finance, IoT, or healthcare.
- Contributions to open-source projects related to LLM technology.
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