LLM Model training for Coding : Full Stack with Javascript/Typescript with 3+ years

3 years

0 Lacs

Posted:2 days ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Contractual

Job Description

Company Description

DeepLLMData specializes in providing high-quality human data to power advanced machine learning models, including Coding SFT and RLHF. The company brings together experts in STEM fields, Mathematics, and domain-specific areas to develop and enhance AI models. DeepLLMData also offers image and video annotation services as well as data provisioning solutions to support cutting-edge AI and machine learning advancements. Our mission is to support innovation by enabling AI models to achieve superior performance across industries.


Role Description

This is a contract-based remote role for a professional with expertise in LLM model training for coding, specifically focused on Full Stack development using JavaScript / TypeScript with 3+ years of experience. The role involves preparing, refining, and delivering code data to train large language models (LLMs). Daily responsibilities include developing high-quality coding examples, collaborating with domain experts, validating coding outputs, and ensuring alignment with the evolving needs of the models. .


Qualifications

  • Strong knowledge and experience in Full Stack development, including JavaScript/TypeScript, with a minimum of 3 years of professional experience.
  • Proficiency in back-end and front-end development with frameworks like Node.js, React, or Angular is preferred.
  • Proficiency in creating, annotating, and testing code-specific datasets for training machine learning models with LLMs.
  • Experience with REST APIs, database integration, debugging, and version control tools (e.g. Git).
  • Excellent problem-solving abilities and communication skills conducive to remote collaboration.
  • Prior experience with model training, coding supervision, supervised fine-tuning, or reinforcement learning is beneficial.
  • A degree in Computer Science, Software Engineering, or a related field is preferred.

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