We are seeking a highly skilled AI Engineer to join our dynamic team. The successful candidate will play a critical role in developing and implementing cutting-edge Natural Language Processing (NLP) techniques to power our AI-driven language learning products. You will work on a variety of applications, including but not limited to:
Automated essay scoring
Pronunciation, grammar, and lexical scoring
AI-based learning assistants
Conversational AI systems
Personalized adaptive learning systems
And more innovative AI-powered education tools
Key responsibilities:
Design, implement, and optimize NLP pipelines for real-world language learning applications
Fine-tune Large Language Models (LLMs) for specialized tasks
Develop agentic systems that support multi-step reasoning, task decomposition, and interactive learning
Utilize Model Context Protocol (MCP) and other LLM orchestration frameworks to build structured, context-aware AI experiences
Collaborate with cross-functional teams including product managers, linguists, and engineers to align AI capabilities with learning goals
Contribute to the evaluation and continuous improvement of model performance using both automated and human-in-the-loop methods
Hard Skills Requirements:
Bachelor's or Master's degree in Computer Science or related fields.
At least 3 years of experience in the field of Natural Language Processing (NLP).
Proficient in programming languages, especially Python (knowledge of C/C++ is an advantage), and capable of using frameworks such as Tensorflow, Keras, PyTorch.
Solid understanding of LLM fine-tuning, prompt engineering, and low-rank adaptation techniques (LoRA, QLoRA, etc.)
Hands-on experience with building or integrating Agentic AI workflows using tool-augmented agents or function-calling
Expertise in building, analyzing data, training, and optimizing NLP models.
Experience in model serving (using RayServe, Triton, TorchServe, etc.) and service integration and deployment is an advantage.
Significant experience with Large Language Models (LLM) is a major advantage.
Proficient use of Git, Docker.
Experience with data organization systems: Database (Postgres, MySQL), Cache (Redis), Queue (RabbitMQ, Kafka) is an advantage.
Ability to comprehend technical documents, scientific articles, and stay up-to-date with the State of The Art (SOTA).
Strong analytical and problem-solving skills.
Soft Skills Requirements:
High enthusiasm and responsibility.
Good communication skills, proactive, flexible at work, collaborative, and friendly within the team.
Careful in work and considerate of customers.
Fluency in English and Chinese is an advantage.
Proficient in programming languages, especially Python (knowledge of C/C++ is an advantage), and capable of using frameworks such as Tensorflow, Keras, PyTorch.
Solid understanding of LLM fine-tuning, prompt engineering, and low-rank adaptation techniques (LoRA, QLoRA, etc.)
Hands-on experience with building or integrating Agentic AI workflows using tool-augmented agents or function-calling
Expertise in building, analyzing data, training, and optimizing NLP models.
Experience in model serving (using RayServe, Triton, TorchServe, etc.) and service integration and deployment is an advantage.
Significant experience with Large Language Models (LLM) is a major advantage.
Proficient use of Git, Docker.
Experience with data organization systems: Database (Postgres, MySQL), Cache (Redis), Queue (RabbitMQ, Kafka) is an advantage.
Ability to comprehend technical documents, scientific articles, and stay up-to-date with the State of The Art (SOTA).
Strong analytical and problem-solving skills.
Note:
By submitting a CV/Resume, along with the information provided by the applicant, and any exchanges during the interview process with Prep (if applicable), the applicant AGREES to Prep's Privacy Policy and the handling of personal data, which is established and issued in accordance with Decree No. 13/2023/NĐ-CP on personal data protection. Additionally, the applicant agrees to allow Prep to collect and store the information provided for the following purposes:
× Collecting personal data and selecting candidates for interviews;
× Contacting and notifying the applicant;
× Assessing the applicant's suitability to select the appropriate candidate for the company's current position.
KPI bonus based on work results and company revenue (2-4 million/month), paid in monthly salary.
Salary increases based on performance and contribution.
Flexible working hours, a youthful and dynamic work environment.
Health insurance, team building activities, annual vacations.