[Remote] Senior AI Engineer

• Working mode: Remote (The candidate must be based in Vietnam)
• Interview process: Technical test (take home assignment) => Final technical interview
• Language: English
• Salary Package: Competitive gross salary + Performance Bonus
• Working hours: Mon-Fri 9AM - 6PM SGT / VNT
• Team size: 46 people. The tech team is about 20; AI team about 4
• Report to: CAIO, CTO, COO

Must-have:

• 5+ years of hands-on experience in AI/ML engineering, ML systems, or data engineering, with proven experience deploying AI/ML products to production.
• Strong proficiency in Python , with experience in PyTorch, TensorFlow, and Hugging Face.
• Practical experience with LLM/SLM fine-tuning, RAG, prompt engineering, and model evaluation.
• Hands-on experience with Agentic AI frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, or CrewAI.

Benefits:

• Competitive gross salary package, inclusive of taxes and insurance.
• Performance-based bonus.
• Annual leave according to company policy.
• Annual performance review.
• Opportunity to work on advanced AI technologies and build production-grade AI solutions.
• A collaborative environment focused on innovation in education technology.

About the Client

Our client is an innovative EdTech company leveraging artificial intelligence to transform teaching and learning across K–12 education, higher education, and corporate training.

Its AI-powered platform combines digital assessments, personalised adaptive learning, and intelligent content generation to help educators create engaging learning materials and deliver tailored learning experiences. By integrating AI-generated knowledge points, knowledge graphs, and a verified knowledge base, the platform enables dynamic learning pathways that improve learning efficiency, personalisation, and transparency.

The company has received multiple industry recognitions and innovation grants for its contributions to education technology.

About the Role

Our client is looking for a Senior AI & Machine Learning Engineer to lead the design, architecture, and deployment of intelligent systems that power personalised learning experiences at scale.

You will drive AI/ML innovation across LLMs, Agentic AI, NLP, recommendation systems, and adaptive learning algorithms. Working closely with product, engineering, and business stakeholders, you will shape technical direction, build reliable production-grade AI solutions, and mentor junior engineers.

This role is ideal for an experienced AI/ML engineer who enjoys solving complex technical challenges and applying advanced AI technologies to real-world educational applications.

Key Responsibilities

• Lead the design, development, and deployment of scalable, production-grade AI/ML models and systems.
• Architect end-to-end AI/ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring (MLOps).
• Research and experiment with LLMs, Agentic AI, NLP, recommendation systems, and adaptive learning algorithms.
• Develop and optimise LLM/SLM applications, including fine-tuning, RAG pipelines, and intelligent AI agents.
• Design and implement knowledge graphs, graph databases, and domain-specific knowledge structures to support intelligent learning systems.
• Collaborate with product, engineering, and business teams to translate user needs into measurable AI-powered solutions.
• Mentor junior AI/ML engineers and establish best practices for code quality, testing, reproducibility, and responsible AI.
• Monitor and optimise deployed models to ensure performance, reliability, scalability, and continuous improvement.
• Evaluate emerging AI technologies, tools, and frameworks to enhance the platform's capabilities.
• Contribute to technical roadmaps, architectural decisions, and the long-term AI strategy.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• 5+ years of hands-on experience in AI/ML systems or data engineering, with a proven track record of bringing AI/ML products into production.
• Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, and Hugging Face.
• Proven experience fine-tuning and evaluating LLMs/SLMs using domain-specific data, including RAG, prompt engineering, and model benchmarking.
• Strong experience with Agentic AI frameworks and patterns, including multi-agent orchestration, tool use, planning, and expert routing.
• Hands-on experience with knowledge graphs and graph databases, including ontology modelling and schema design.
• Experience with multimodal AI, particularly speech processing (ASR, prosody) and/or computer vision (OCR, handwriting recognition, diagram understanding), is highly desirable.
• Demonstrated ability to mentor engineers and lead technical initiatives from concept to delivery.
• Strong problem-solving, communication, and cross-functional collaboration skills.
• Genuine interest in education and applying AI to improve learning outcomes.