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At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.

The Mission

Make general-purpose robots a reality via large-scale embodied AI.

The Challenge

We envision a future where robots assist with household chores and cooking, aid the elderly in maintaining their independence, and enable people to spend more time on the activities they enjoy most. To achieve this, robots need to be able to operate reliably in messy, unstructured environments. Our mission is to answer the question “What will it take to create truly general-purpose robots that can accomplish a wide variety of tasks in settings like human homes with minimal human supervision?”. To answer this, we are gathering large datasets of physical interaction from a variety of sources (including robots and people) and training large generative foundation models on this physical interaction data along with language, video, audio, and other rich modalities.

The Team

Our goal is to revolutionize the field of robotic manipulation, enabling long-horizon dexterous behaviors to be efficiently taught, learned, and improved over time in diverse, real-world environments. Our team has deep cross-functional expertise across simulation, perception, controls, language, vision, multimodal learning, and generative modeling. Success is measured by the advancement of robot capabilities and we’re strong believers in open research. Our north star is fundamental technological advancement in building robots that can flexibly perform a wide variety of tasks in diverse environments with minimal human supervision. Come join us and let’s make general-purpose robots a reality!

We operate a fleet of robots, and robot-embodied teaching and deployment are key parts of our strategy. Some of our previous work is highlighted here.

The Opportunity

We’re looking for a driven Staff Software Engineer comfortable working on large integrated machine learning systems. Experience with robots or other embodied systems (such as autonomous vehicles) is a bonus. You will play a pivotal role in designing, building, and optimizing pipelines that support large behavior models. You will collaborate with a team of researchers and engineers to develop resilient, scalable, and impactful systems. This role requires technical leadership, hands-on development, and strategic thinking.

If our mission of revolutionizing robotics through machine learning resonates with you, get in touch and let’s talk about how we can create the next generation of AI-powered capable robots together!

• Architect and implement large-scale software systems for behavior modeling and decision-making in robotics.
• Develop tools, frameworks, and pipelines to train, evaluate, and deploy models efficiently.
• Mentor junior engineers and provide guidance on best practices in software development and machine learning.
• Contribute to technical strategy and decision-making for the LBM team.
• Partner with researchers to translate cutting-edge algorithms into production-quality systems.
• Work cross-functionally with simulation, hardware, perception, and control teams to integrate LBM capabilities into embodied systems.
• Improve the scalability, robustness, and efficiency of large behavior models for real-world applications.
• Identify and address bottlenecks in data pipelines and model performance.

• 8+ years of professional experience in software engineering, with a focus on robotics, machine learning, or distributed systems.
• Demonstrated success in leading technical projects and delivering impactful solutions.
• Familiarity with the state-of-the-art in behavior learning, language, and/or computer vision.
• Strong proficiency in Python and software development best practices such as unit testing, documentation, code review, continuous integration, and dependency management.
• Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management.
• An ability to move fast and switch between modes of rapid prototyping and robust implementation as required.
• Strong mentorship abilities and a track record of technical leadership.
• Excellent problem-solving skills and a proactive mindset.

• Experience deploying models on embodied systems/robots.
• Experience working in mixed teams of research scientists and engineers.
• Experience Amazon EC2, S3, and/or Sagemaker.
• Experience with Bazel.