Robotics Engineer, Foundation Model (Open Position)
Indexed description
As the Robotics Engineer, Foundation Model, you will design, train, and deploy large-scale multimodal models that integrate vision, language, and action components for real-world robotic applications. Leveraging data from our teleoperation systems, you will create generalizable policies for our robots to perform complex tasks autonomously and reliably—beyond lab-scale or proof-of-concept demos. You will guide the end-to-end pipeline, from data processing and model design to on-robot deployment and performance optimization.
This is an open role intended for engineers at wide experience levels, from mid-career engineers to experienced technical leaders.
What You'll Work On
- Design, train, and fine-tune large-scale foundation models (multimodal, transformer-based, and/or Vision-Language-Action models) for robotic perception, reasoning, and control.
- Build and maintain data and training pipelines, including data collection from teleoperation, preprocessing, annotation, and distributed training at scale.
- Collaborate with robotics, controls, and hardware engineers to integrate models into real robot systems and evaluate them in production environments.
- Design experiments and evaluation protocols to measure model performance, safety, and reliability, and iterate based on real-world deployment feedback.
- Optimize models for efficient inference and deployment on embedded/edge hardware.
- Track developments in foundation models, LLMs, multimodal and generative AI research, and assess their applicability to TX's products.
- Background in Machine Learning, Computer Science, Robotics, or a related field.
- Professional experience in machine learning or deep learning engineering, or equivalent research/graduate experience.
- Hands-on experience training, fine-tuning, or serving large-scale models, e.g. LLMs, vision-language models, diffusion models, or other multimodal/foundation models.
- Strong software engineering skills in Python and experience with a deep learning framework (PyTorch preferred).
- Familiarity with large-scale/distributed training and modern ML infrastructure or MLOps practices.
- Strong problem-solving skills and ability to work in cross-functional teams.
- Robotics (ROS/ROS2), reinforcement learning, or embodied AI
- Vision-Language-Action (VLA) or other multimodal foundation models
- Deploying models to edge devices such as NVIDIA Jetson
- Computer vision, NLP, or generative modeling research
- Control theory, teleoperation systems, or actuator/hardware integration
- Publications, open-source contributions, or a portfolio of applied ML/AI work
We welcome applications from engineers at wide career stages. The scope and level of responsibility will be aligned with your experience and expertise.
Language
- Professional proficiency in English required.
- Japanese language skills are a plus.
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