VP, Robotics Foundation Models

Location: Tokyo, Japan (Hybrid)
Employment Type: Full-Time
Visa Sponsorship: Available for international candidates and eligible family members

About the Opportunity

A rapidly growing robotics and AI company is seeking a VP of Robotics Foundation Models to lead the strategy, organisation, and technical execution of a world-class team building next-generation embodied AI systems.
This executive leadership role is responsible for defining and scaling the company's robotics foundation model initiatives, transforming cutting-edge multimodal AI research into robust real-world robot capabilities deployed in production environments.
The successful candidate will lead a multidisciplinary organisation spanning robotics, machine learning, AI research, data infrastructure, teleoperation, controls, hardware, and product engineering. You will be responsible for building high-performing teams, establishing technical direction, developing long-term roadmaps, and delivering scalable AI systems that directly impact physical robotic platforms operating in real-world environments.
This is an opportunity to shape the future of embodied intelligence by developing foundation models that integrate vision, language, robot state, and action into unified systems capable of complex autonomous behaviour.

Key Responsibilities

Organisational Leadership

Build, lead, and scale a high-performing Robotics Foundation Model organisation.
Recruit, mentor, develop, and retain exceptional engineers, applied scientists, and research talent.
Establish operational excellence across planning, technical reviews, execution, deployment, and performance management.
Partner closely with executive leadership to align technical investments with business objectives.

Technical Strategy

Define the long-term vision and roadmap for robotics foundation models.
Drive architecture decisions across multimodal AI systems combining vision, language, robot state, and action.
Balance research innovation with practical deployment requirements.
Guide model scaling strategies, fine-tuning approaches, evaluation methodologies, and production readiness.

AI & Robotics Systems

Lead development of large-scale multimodal foundation models for robotic applications.
Drive integration of AI systems with perception, control, manipulation, and autonomy stacks.
Ensure models operate reliably and safely on physical robots in real-world environments.
Support deployment to embedded and edge computing platforms.

Data Strategy

Define end-to-end data acquisition strategies leveraging teleoperation, robot operation, and multimodal sensor streams.
Oversee data collection, curation, annotation, quality assurance, and dataset governance.
Build pipelines that convert large-scale robotic datasets into training-ready assets.
Establish continuous learning frameworks to improve model performance from deployment feedback.

Deployment & Evaluation

Define evaluation frameworks and KPIs for model quality, autonomy, robustness, and operational performance.
Lead root-cause analysis and continuous improvement processes for deployed robotic systems.
Establish standards for reproducibility, safety, reliability, and scalability.

Cross-Functional Leadership

Collaborate with robotics, hardware, controls, infrastructure, platform, and product teams.
Act as the senior technical leader and subject matter expert for robotics foundation models.
Represent the organisation with research partners, customers, vendors, and external technical stakeholders.

Required Qualifications

Leadership Experience

Proven experience leading high-performing machine learning, robotics AI, or foundation model teams.
Track record managing large-scale engineering and research organisations.
Experience defining technical roadmaps, allocating resources, and driving execution across complex programmes.
Ability to balance deep technical involvement with executive-level leadership responsibilities.

AI & Foundation Models

Deep expertise in multimodal AI systems, including:
- Vision-Language Models (VLMs)
- Vision-Language-Action Models (VLAs)
- Transformer-based architectures
- Foundation Models
- Representation Learning
Strong experience with:
- Model training and evaluation
- Fine-tuning and adaptation
- Distributed training systems
- Inference optimisation
- Large-scale AI infrastructure

Robotics

Experience deploying AI systems on real robotic platforms.
Knowledge of:
- Robot manipulation
- Robot learning
- Autonomous systems
- Perception systems
- Motion planning
- Teleoperation systems
Strong understanding of robotics software ecosystems including:
- ROS / ROS2
- Embedded AI deployment
- Edge computing platforms (e.g. Jetson)

Data & Platforms

Extensive experience managing large multimodal datasets containing:
- Images
- Video
- Text
- Sensor logs
- Robot trajectories
Strong understanding of production ML systems and distributed infrastructure.

Preferred Backgrounds

Candidates may currently hold titles such as: