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ABOUT VINDYNAMICS

At VinDynamics, we design safe, affordable, and intelligent humanoid robots to assist in everyday life — robots for everyone. Backed by Vingroup, Vietnam’s leading technology conglomerate, we are on a mission to make advanced robotics accessible, reliable, and beneficial for billions of people worldwide. By combining cutting-edge AI, world-class engineering, and human-centered design, we aim to seamlessly integrate robots into daily life — enhancing safety, productivity, and happiness at home and beyond.

JOB DESCRIPTION

Cognitive Architecture & Agent Design

• Design and define the agentic cognitive architecture for humanoid robots.

• Build reasoning, planning, and decision-making systems powered by LLMs.

• Develop hierarchical goal decomposition and task execution mechanisms.

• Design and implement robot memory systems (episodic, semantic, and working memory).

Grounding & Autonomy

• Ground language reasoning into perception signals and robot control actions.

• Build closed-loop perception–reasoning–action systems for real-world autonomy.

• Define evaluation metrics for autonomy, robustness, latency, reliability, and safety.

Research & Deployment

• Publish high-impact research and contribute to the global AI & robotics community.

• Translate research breakthroughs into scalable production systems.

• Collaborate closely with Vision, Conversation AI, Control, and System Engineering teams to integrate agentic intelligence into deployed humanoid robots.

REQUIREMENTS

Education & Background

• Master’s or PhD in Artificial Intelligence, Machine Learning, Robotics, or related fields.

• Strong hands-on experience with LLMs, agent architectures, and decision-making systems.

• Proficiency in Python (PyTorch required).

• Strong system-thinking mindset and rigorous experimental design capability.

Core Expertise

• Agentic AI architectures: Planner–Executor loops, ReAct-style agents, multi-agent systems, goal decomposition, task orchestration.

• LLM reasoning & alignment: Instruction tuning, safety alignment, hallucination mitigation, controllable generation.

• Memory systems: Short-term memory, long-term memory, episodic memory, semantic knowledge graphs, retrieval-augmented reasoning.

• Multimodal grounding: Connecting language ↔ vision ↔ robot state ↔ action in closed-loop systems.

Preferred Qualifications

• Research publications in top-tier venues such as NeurIPS, ICLR, ICML, RSS, or ICRA.

• Experience with:

  • Retrieval-Augmented Generation (RAG) / memory-augmented agents

  • Tool-use and API-driven agents

  • Multimodal agents (vision + language + action)

• Knowledge of:

  • Reinforcement Learning, RLHF, or preference learning

  • Safety, alignment, and failure recovery mechanisms for autonomous agents

Personality & Attitude

• Proactive, responsible, and impact-driven with a strong business mindset.

• Excellent communication and cross-functional collaboration skills.

• Strong problem-solving capability and system-level thinking.

• Comfortable working at the frontier of research with evolving constraints.

BENEFITS & COMPENSATIONS 

• Attractive income, competitive and commensurate with individual capabilities. 

• 13th-month salary, gifts on public holidays and special occasions, and performance-based bonuses. 

• Meal allowance, annual company trips, health insurance, and exclusive benefits within the Group’s ecosystem 

• Clear career development opportunities aligned with the company’s growth, with access to training programs based on capability and job role.