**Company: G-Talent Job Description Summary: The company G Talent is seeking a Machine Learning Engineer with experience in Natural Language Processing (NLP) and Generative AI products. They are a well-known start-up with a global presence and offer a competitive salary. The company works on various AI projects across industries and is highly rated as a great place to work. The job involves working with NLP technology, collaborating with AI consultants, and developing machine learning models. Opportunities in this position include gaining domain knowledge, deepening skills in generative AI, and interacting with NLP communities. Career progression options include Tech Lead, Engineering Manager, and Product Manager roles. Requirements include a willingness to commit, proficiency in English papers on machine learning, experience with machine learning tools, and programming skills. Other preferred qualifications include cloud platform experience, product development experience, and management experience. The company offers a discretionary labor system, full holiday system, paid leave, social insurance, and other benefits. The ideal candidate should have at least five years of experience in the field. Job Description: ★ Machine Learning Engineer(NLP/Generative AI Product) | Featured AI company • Intermediate Level Japanese Required ◆ Famous Start-up Company ◆ Hybrid Work ◆ Global Business ◆ Own Product / Service ◆ Annual Salary： 6 million ～ 10 million yen. ————-【About the company】————- The company has engaged in various industry AI projects. We have clients in a wide range of industries, such as finance, manufacturing, retail, food and drink, education, healthcare, manufacturers and IT communications, with hundreds of cases. The company is rated as one of the Best Ventures to Work in Japan. Based on the knowledge and know-how of each industry obtained from this wide network, we promise innovative proposals that exceed the industry and precedent. Many intelligent talents in the world are gathering into the company now. ————-【 Job Description】————- The company’s engineers are divided into teams (guilds) in one of the following areas of technical expertise… image processing, structured data processing, natural language processing, mathematical optimization, and Robot &Automation, where they implement and improve learning models and algorithms. In this position, you will work with natural language processing technology. In collaboration with the company’s AI consultants, you will be involved in projects to solve customer issues using natural language processing technology, or in product development through the development of machine learning models. 【Oppotunities you will get in this position】 ・You can catch up on domain knowledge as well as technical knowledge, as our project work to solve clients’ problems covers multiple industries (multi-sector) and requires extensive knowledge of machine learning and natural language processing. ・You can deepen your knowledge of generative AI technologies by actively investing in the development of products that utilize generative AI, such as GPT. ・Sponsorship of the Association for Natural Language Processing and the Young Adult NLP Society (YANS) provides opportunities to interact with external communities related to NLP. ・NLP has speech engineers on staff, and you can be involved in research and development in the field of speech if you wish. ・Multiple machine learning related teams (image/optimization/structured data), so you can deepen your knowledge of a wide range of machine learning by collaborating with other guilds. ・Prof. Jun Suzuki, Professor of Graduate School of Information Science and Technology, Tohoku University, serves as an advisor and provides seminars and technical consultation opportunities. 【Career Steps】 ・In addition to building a career in the technical area as a Tech Lead, you can also gain management experience as an Engineering Manager (EM) or Product Manager (PdM). ————-【 Requirements】————- 【Required】 ・Willingness to commit to society and business ・Ability to read English papers on machine learning/deep learning and understand and implement the algorithms ・Experience using machine learning/deep learning tools or libraries ・Experience programming in Python or other languages 【Preferred】 ・Experience using AWS, Google Cloud, and other cloud environments ・Experience in product development ・Experience accepting papers for international conferences ・Experience in management ————————————————– Discretionary labor system (You can come office and go home anytime!!) ・Full holiday 2 day system (Saturday / Sunday) holidays ・Refresh leave ・Annual paid leave ・Return leave ・Congratulations & Condolence Leave ・Parental leave ・Nursing care leave ・Others ・Full Social Insurance ・Commuting Allowance ・Medical Checkup
Company:G Talent
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Level of experience (years):Senior (5+ years of experience)
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
