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Mô Tả Công Việc
● Identify and extract the data needed to solve the problem
● Clean up and analyse the quality of unstructured data
● Implement data science solutions and build state-of-the-art ML/AI models
● Evaluate the performance of ML/AI models, put them in production and manage their life cycle
● Build modern day application with Generative AI tools (OpenAI APIs or PaLM 2 APIs from Google)
● Fine tuning Large Language Models
● Contribute to the implementation of a robust, efficient and easy to use tool set
Yêu Cầu Công Việc
● Bachelor or Master in Computer Science / Data Science or other relevant fields. English communication is required.
● Proficient in Python, SQL and PyTorch/TensorFlow.
● At least three-year working experience in Machine Learning and Natural Language Processing / Deep Learning related fields.
● Hands on experience with Generative AI tools (OpenAI APIs or PaLM 2 APIs from Google)
● Experience with tuning Large Language Models (Good to have)
● Familiar with one the NLP tools-suit is preferred, such as regex, spaCy, nltk, and Stanford NLP tools;
● Familiar with the state-of-the-art deep models such as BERT, GTP and beyond;
● Experience in some of the following domains: language model / text classification / text clustering /
named entity recognition etc.
● Familiar with the data analysing tools such as pandas, numpy;
● Experience in building machine learning pipelines is a plus.
● Analyze business problems, design solutions, deploy solutions as inference APIs / pipelines, maintain
solutions and improve models
Hình thức
Quyền Lợi
- Attractive salary package
- Probation period: 2 months and you will receive 100 % of the salary
- 14 days annual leave. And will have 1 more day annual leave for each year working with the company.
- Full coverage insurance
- Modern, open and comfortable working environment
- Well-equipped entertainment room ( Table tennis, billiards, weight …)
- Creative and friendly colleagues, enthusiast and supportive management
- Free drink and snack
- Fruit party every Friday
