AI Engineer (VLAs)
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Overview
Description
Required Skills
- 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 Skills
- 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
About AI Robot Association (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
Quick Facts
Submit your application for this role at AI Robot Association (AIRoA).