AI Architect - Remote Hanoi-based (VinDynamics)

The role is to lead the technical design and integration of the AI Agent brain of next-generation robotic assistants. This role ensures that AI models are strategically architected and optimized to run reliably on robotic hardware with high performance, ensuring high-quality human–robot interaction in real-world applications.

REQUIREMENTS

Education & Experience

• Bachelor’s of Engineering in Engineering, Automation, Computer Science (or related field) from a top-tier technical university.
• At least 6 years of experience in leading, designing, researching, and deploying secure, scalable AI solutions.
• Expertise in multilingual NLP, LLM/VLM, and advanced Retrieval-Augmented Generation (RAG).
• Proficiency in Python, C/C++, and deep learning frameworks like PyTorch and TensorFlow.
• Expertise in Computer Vision and Machine Learning for large-scale AI systems.
• Hands-on experience with cloud platforms (AWS, GCP, Azure) and CI/CD pipelines.

Preferred Qualifications (Nice to Have)

• Published research in AI/ML related to local Vietnamese information recognition or joint learning models.
• Experience with leading and designing the development of large-scale agentic AI chatbots and multi-agent system architectures.
• Possesses relevant AI/ML professional certifications or coursework.

Personality & Attitude

• Strong system-thinking mindset and experimental rigor, with strong leadership in leading AI and cross-functional engineering teams.

JOB DESCRIPTION

Key Responsibilities

• Design the AI system architecture, managing hardware constraints and ensuring seamless integration with the Robot OS.
• Lead the technical architecture for performance optimization using C++ to meet the 0.5s response time goal.
• Manage model selection and customization, evaluating optimal architectures for real-time humanoid applications.
• Define RAG and multimodal AI reasoning frameworks to connect language understanding with situational awareness.

Collaborate with ROS2, control, and system engineering teams to ensure the AI brain is optimized for physical robot deployment.