AI Engineer (VLAs)

Description

About AIRoA

The AI Robot Association (AIRoA) is launching a groundbreaking initiative: collecting one million hours of humanoid robot operation data with hundreds of robots, and leveraging it to train the world’s most powerful Vision-Language-Action (VLA) models.

What makes AIRoA unique is not only the unprecedented scale of real-world data and humanoid platforms, but also our commitment to making everything open and accessible. We are building a shared “robot data ecosystem” where datasets, trained models, and benchmarks are available to everyone. Researchers around the world will be able to evaluate their models on standardized humanoid robots through our open evaluation platform.

Job Description

Develop Vision-Language models, or equivalent multimodal models, with a view toward applications in the robotics domain

Fine-tune existing models, conduct evaluations, perform error analysis, and improve performance

Build training pipelines using real-world data, design evaluation metrics, and operate iterative improvement cycles

Prepare and preprocess data, and build training environments for image, video, language, and action data

Research the latest trends in technologies and academic studies, select appropriate technologies, and incorporate findings into model improvements

Establish training infrastructure, inference infrastructure, and experimental environments for real-world model deployment

Collaborate with related teams such as software engineers and robotics engineers to define requirements, design validation plans, and drive development

Requirements

Required Qualifications

Experience leading machine learning models from deployment to improvement and operation in a production service environment

Experience implementing, training, and evaluating machine learning models using Python and PyTorch

Hands-on experience fine-tuning Vision-Language models, or equivalent multimodal models

Experience building training pipelines with real-world data, designing evaluations, conducting error analysis, and operating improvement loops

Ability to understand the latest research and technology trends and translate them into model improvements and practical product applications

Preferred Qualifications

Experience developing Vision-Language-Action (VLA) models or multimodal models for robotics

Experience with robot control, ROS / ROS 2, C++, and real-world hardware evaluation

Knowledge of or experience in sensor integration, actuator control, action generation, and low-level control

Familiarity with training and evaluation using simulators, Sim2Real, and domain adaptation

Experience building training and inference infrastructure in cloud environments such as AWS or GCP

Experience with reproducible and operationally robust development practices such as Docker, CI/CD, and MLOps