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.
VinDynamics is building general-purpose humanoid robots powered by large-scale learning systems. We are seeking an MLOps Engineer to design and operate the infrastructure, pipelines, and tooling that enable reliable training, evaluation, deployment, and monitoring of AI models across simulation and real robots.
This role sits at the intersection of ML, systems engineering, and robotics, ensuring that models—ranging from Vision-Language-Action (VLA) to reinforcement learning and diffusion-based policies—can be trained at scale, reproduced reliably, and deployed safely to humanoid platforms.
Design and maintain end-to-end ML pipelines: data → training → evaluation → deployment.
Build infrastructure for large-scale model training (on-prem GPU clusters and hybrid cloud).
Support training and evaluation of:
VLA and multimodal foundation models
RL and imitation learning policies
Diffusion / flow-matching action models
Implement experiment tracking, model versioning, and reproducibility.
Manage model packaging, deployment, and rollback for simulation and real robots.
Develop monitoring and alerting for model performance, drift, and failures.
Optimize training and inference workflows for performance, cost, and reliability.
Collaborate closely with Data, AI Manipulation, Autonomy, Simulation, and Hardware teams.
Bachelor’s / Master’s degree in Computer Science, ML, Robotics, or related fields.
Strong experience in MLOps, ML infrastructure, or platform engineering.
Proficiency in Python; familiarity with ML frameworks (e.g., PyTorch).
Experience managing GPU-based training workloads.
Solid understanding of ML lifecycle management (training, evaluation, deployment).
Experience with containerization and automation.
Preferred Qualifications
Experience supporting robotics or embodied AI systems.
Familiarity with reinforcement learning or multimodal models.
Experience with distributed training and large models.
Knowledge of experiment tracking, model registries, and CI/CD for ML.
Experience deploying models to real-time or safety-critical systems.
Competitive compensation package based on experience and qualifications
Work in a high-speed technology environment backed by Vingroup and VinDynamics leadership.
Competitive compensation package aligned with capability and business impact.
Clear ownership, measurable KPIs, and exposure to global partners, US platform models, and frontier robotics businesses.
Nguồn: careers VinDynamics
