Our mission is to make robotics an irreversible reality. We are always interested in connecting with talented Foundation Model Engineers who are passionate about building the AI that powers real-world robots.
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.
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.
Experience in one or more of the following areas:
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
You will have the opportunity to work on foundation models that don't just predict text or images but move real robots in real stores and warehouses, collaborating with multidisciplinary teams to bring next-generation physical AI from prototype to real-world deployment.
We welcome applications from engineers at wide career stages. The scope and level of responsibility will be aligned with your experience and expertise.
Professional proficiency in English required.
Japanese language skills are a plus.
“TELEXISTENCE” is a concept that was first proposed in 1980 by Dr. Susumu Tachi, Professor Emeritus of the University of Tokyo and the chairman of TX inc, which refers to the notion of humans being in a place other than where he or she actually exists and being able to act freely in that remote environment – essentially expanding the presence of human beings – as well as the technological systems that make this possible.
Our mission at TX inc is to change robotics, change structures, and change the world.
テレイグジスタンス（TELEXISTENCE/遠隔存在）とは、TX incの創業者の一人でTX会長でもある東京大学名誉教授 舘暲氏が1980年に世界で初めて提唱した、人間が、自分自身が現存する場所とは異なった場所に実質的に存在し、その場所で自在に行動するという人間の存在拡張の概念であり、また、それを可能とするための技術体系です。 TX incのミッションは、ロボットを変え、構造を変え、世界をかえることです。
