Key Responsibilities

• Design, implement, and maintain large-scale ML pipelines and optimize model performance for training on massive robot datasets
• Design, deploy, and maintain distributed training clusters to reduce model development cycles
• Collaborate closely with VLA researchers to capture evolving ML infrastructure, data pre-processing, training, monitoring, evaluation, and deployment requirements and continuously improve ML pipeline through analysis and experimentation.
• Optimize ML infrastructure and pipeline for cost, performance, and reliability
• Design, develop, and maintain MLOps tools and platforms to ensure VLA researchers can efficiently visualize and analyze the performance

Requirements

Required Qualifications

• Master’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• 5+ years of professional experience as a software engineer in MLOps engineering, machine learning, or robotics.
• Experience in deploying distributed systems to popular cloud services such as AWS, GCP, Azure.
• Experience in orchestration tools such as Airflow, Dagster, or Kedro.
• High proficiency in PyTorch or JAX.

Preferred Qualifications

• Experience with training and fine-tuning techniques for RL, VLM, and VLA models, including distillation, supervised fine-tuning, and policy optimization.
• Experience building ETL/ELT pipelines for data processing.
• Experience in hyper-parameter optimization.
• Experience in distributed training frameworks and cluster management for deep neural network training.
• Deep understanding of GPU memory management and optimization techniques.
• Experience in analyzing, monitoring, and managing data quality.
• Experience with processing robotics-related sensor data (e.g., RGB/Depth images, point clouds), including knowledge of image/signal processing, sensor fusion, and time synchronization.
• Experience with ROS/ROS2.
• High proficiency in SQL.
• Experience optimizing system performance using performance analysis tools.

Others (linguistic qualification, etc.)

【Highly appreciated】
English proficiency at business level

Benefits

There are currently no comparable projects in the world that collect data and develop foundation models on such a large scale. As mentioned above, this is one of Japan’s leading national projects, supported by a substantial investment of 20.5 billion yen from NEDO.

This position will play a crucial role in determining the success of the project. You will have broad discretion and responsibility, and we are confident that, if successful, you will gain both a great sense of achievement and the opportunity to make a meaningful contribution to society.

Furthermore, we strongly encourage engineers to actively build their careers through this project—for example, by publishing research papers and engaging in academic activities.

●Work location

Tokyo Ryutsu Center A Bldg. AW4-5, 6-1-1 Heiwajima, Ota-ku, Tokyo 143-0006, Japan