Large Language Model Research Intern

1 week ago

Beijing, Beijing, China Cummins Inc. Full time

Position Overview

The Cummins Data Science and Artificial Intelligence Department is looking for undergraduate or graduate students to engage in comprehensive research opportunities. These roles will focus on the exploration and practical application of Large Language Models (LLM) within the automotive and industrial sectors.

Key Responsibilities

  • Investigate application scenarios for Large Language Models in automotive and industrial contexts.
  • Design and develop frameworks tailored for Large Language Models in specific verticals.
  • Construct and enhance applications leveraging Large Language Models.
  • Assess and analyze the performance of Large Language Models in targeted domains.

Main Duties

  • Gather and organize domain-specific data: Collect relevant texts, codes, and datasets from the automotive and industrial fields, ensuring they are cleaned, annotated, and compiled to create a high-quality database for LLM training and application.
  • Develop and implement application solutions utilizing Large Language Models: Create tailored solutions based on LLMs for specific use cases, such as intelligent customer service systems, automated Q&A systems, and fault diagnosis systems.
  • Optimize the training and inference processes of Large Language Models: Enhance the efficiency, accuracy, and interpretability of the model's training and inference stages.
  • Evaluate and analyze the effectiveness of Large Language Models: Conduct assessments of LLM performance in automotive and industrial applications, refining and improving them based on findings.
  • Produce technical documentation and reports: Document the research and development processes related to LLM applications in automotive and industrial settings, detailing outcomes and lessons learned.
  • Present compelling narratives to team members and stakeholders throughout the internship and at its conclusion.

Qualifications and Skills

  • Currently pursuing an undergraduate or graduate degree in Computer Science, Data Science, Artificial Intelligence, or related fields: Strong foundation in computer science principles and familiarity with data structures, algorithms, and programming languages.
  • Understanding of Natural Language Processing (NLP) technologies: Knowledge of fundamental NLP concepts, including word embeddings, language modeling, text classification, and machine translation.
  • Familiarity with Large Language Model (LLM) technologies: Comprehension of core concepts and application frameworks associated with LLMs, including Transformers, pre-trained models, prompt engineering, retrieval-augmented generation, fine-tuning, and LangChain.
  • Experience deploying major open-source LLMs, such as ChatGLM and Llama.
  • Relevant project experience: Involvement in NLP or LLM-related projects, such as chatbots, text generation, or Q&A systems.
  • Proficiency in Python or other programming languages: Capable of writing and developing code effectively in Python or similar languages.
  • Strong learning and problem-solving abilities: Quick to acquire new knowledge and technologies, with the capacity to address challenges independently.
  • Excellent communication and teamwork skills: Ability to effectively collaborate with team members and contribute to project objectives.

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