VinDynamics
AI tóm tắt
Skills bắt buộc
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 Summary:
We are seeking a Senior AI System Architect to own the end-to-end architectural design of our AI systems powering humanoid robots. You will define how LLM/GenAI capabilities are embedded into robot cognition, how AI workloads are distributed across cloud and edge infrastructure, and how our AI platform supports scalable model development and deployment. This is a pure architecture role — you will set the technical direction, produce authoritative design artifacts, and guide engineering teams without being responsible for day-to-day implementat.
Relevant education and experience
Bachelor's degree or higher in Computer Science, AI/ML, Software Engineering, or related fields. Master's or PhD preferred.
5+ years of experience in software or systems engineering, with at least 2+ years in a dedicated architecture or technical design role.
LLM / GenAI: Deep understanding of large language model architectures, prompt engineering, RAG (Retrieval-Augmented Generation), function calling, multi-modal models, and agentic AI patterns. Hands-on familiarity with leading platforms (OpenAI, Gemini, Claude, open-source LLMs).
·Cloud / Edge AI: Strong grasp of cloud AI services (AWS, GCP, or Azure AI stacks) and edge inference frameworks (TensorRT, ONNX Runtime, TFLite); ability to design cost-efficient, latency-aware hybrid architectures.
AI Platform & MLOps: Architectural knowledge of ML lifecycle tooling — Kubeflow, MLflow, Weights & Biases, or equivalent; CI/CD for ML; model monitoring and drift detection.
System Design: Proficient in distributed systems design — microservices, event-driven architectures, API gateway patterns, message queues (Kafka, MQTT, or equivalent).
Infrastructure Concepts: Solid understanding of containerization (Docker, Kubernetes), networking fundamentals, and cloud-native design principles.
Preferred Qualifications
Experience with real-time AI systems and latency-constrained inference design.
Knowledge of AI safety frameworks, responsible AI governance, and model risk management.
Exposure to multi-agent AI systems or autonomous decision-making architectures.
Personality/ Attitude
Senior mindset: Takes ownership of complex problems end-to-end, drives solutions without needing close supervision.
Detail-oriented: Produces clean, well-documented code and integration specs that others can build on.
Collaborative: Works effectively across engineering, product, and customer-facing teams.
AI Architecture Design
Define the overall AI system architecture for VinDynamics robots — covering inference pipelines, model serving, data flows, and system boundaries.
Architect the integration of LLM and GenAI models into robot cognition layers — including prompt orchestration, context management, multi-modal input handling (vision + language), and real-time response latency management.
Design agentic AI frameworks that allow robots to plan, reason, and act using foundation models in dynamic real-world environments.
Establish architectural standards for AI API contracts between robot runtime, edge nodes, and cloud services.
Cloud / Edge AI Infrastructure
Design hybrid cloud-edge AI architectures that balance latency, bandwidth, and compute constraints specific to humanoid robot deployments.
Define infrastructure blueprints for on-device AI inference (edge) and offloaded workloads (cloud) — including failover, fallback, and graceful degradation strategies.
Architect secure, low-latency communication layers between robot fleets and AI backend services.
Define compute and networking requirements in collaboration with infrastructure and DevOps teams.
AI Platform & MLOps Architecture
Design the AI platform architecture that supports the full model lifecycle — data ingestion, training, evaluation, versioning, deployment, and monitoring.
Define MLOps workflows and toolchain standards (experiment tracking, model registry, deployment pipelines, A/B testing, observability).
Establish architectural guardrails for responsible AI — including bias evaluation, safety constraints, and audit logging for production AI systems on robots.
Create reusable platform blueprints that accelerate AI feature delivery across product teams.
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.
A dynamic and open working environment with diverse cultural and sports activities.
Nguồn: careers VinDynamics
