Data Engineer, OneDegree AI

薪資範圍:700,000 ~ 980,000 TWD / year

公司名稱: OneDegree

We are seeking a skilled and motivated individual to join our team as a Data Engineer. The successful candidate will assist in research, support model training, and optimize machine learning solutions. The role requires organizing relevant data, analyzing test results, and fine-tuning models. Additionally, the candidate will be responsible for analyzing and interpreting large datasets to support our B2B AI large language model (LLM) Verification solution.

OneDegree Tech Blog: https://medium.com/onedegree-tech-blog

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    How to apply

    Please apply this position through 👉 https://grnh.se/3d78328e4us

    It will help us process your applications faster
    *Please apply by English CV, thank you.

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    Responsibilities

    1. Assist in Research and Support Model Training:
      1. Provide technical support during the model training phase, ensuring the process runs smoothly and efficiently.
      2. Conduct literature reviews and stay updated with the latest advancements in machine learning and AI.
    2. Evaluate and Optimize Machine Learning Solutions:
      1. Perform thorough evaluations of machine learning models to assess their performance and accuracy.
      2. Implement optimization techniques to enhance model efficiency and effectiveness.
    3. Organize Relevant Data Based on Requirements and Optimize Related Models:
      1. Collect and organize datasets according to project requirements, ensuring data quality and integrity.
      2. Continuously optimize models based on data insights and project needs.
    4. Analyze Test Results and Fine-Tune Models:
      1. Conduct detailed analyses of test results to identify patterns, anomalies, and areas for improvement.
    5. Analyze and Interpret Large Datasets:
      1. Work with large volumes of data to extract meaningful insights that inform model development.

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        1. Proficient in Data Warehousing, Data Preprocessing Concepts, Data Cleaning, Data Preparation, Tokenization, and Related Data.
        2. Skilled in tokenization and transforming raw data into structured formats suitable for machine learning models.
        3. Proficient in Python (including numpy, scipy, pandas) .
        4. Experience with SQL and Database Design (e.g., SQL/NoSQL/Vector DB).
          1. Understanding of database design principles, including both SQL and NoSQL databases.
          2. Familiarity with vector databases and their application in AI and machine learning contexts.
        5. Experience with OpenAI, Langchain, and RAG Architecture:
          1. Hands-on experience with OpenAI technologies and integrating them into machine learning workflows.
          2. Knowledge of Langchain and RAG (Retrieval-Augmented Generation) architecture, and their implementation in practical projects.
        6. Demonstrated ability to analyze large datasets, using statistical and machine learning techniques to derive insights.
        7. Strong Team Collaboration and Self-Learning Abilities:
          1. Proven ability to work effectively in a team environment, collaborating with colleagues to achieve common goals.
          2. Self-motivated with a strong desire to continuously learn and stay updated with the latest industry trends and technologies.

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        Plus

        1. Familiarity with Machine Learning Frameworks (e.g., Keras, TensorFlow, PyTorch) is a Plus:
          1. Experience using popular machine learning frameworks such as Keras, TensorFlow, or PyTorch.
        2. Familiarity with NLU/NLG/NLP Architectures (e.g., BERT, Transformers) is a Plus:
          1. Knowledge of Natural Language Understanding (NLU), Natural Language Generation (NLG), and Natural Language Processing (NLP) architectures.
          2. Understanding of Java programming language and its application in data engineering and machine learning projects.

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        公司地址:

        台北市信義區四段460號7樓

        其他:

        Phone interview: 1 hour meet with HROnsite Interview: 1-2 hours1-1.5 hours meet with our team and hiring managers0.5 hour meet with HR-2024-09-17
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