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, and Robotics.
The Mission
Make general-purpose robots a reality.
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?”. We believe that the answer lies in cultivating large-scale datasets of physical interaction from a variety of sources and building on the latest advances in machine learning to learn general purpose robot behaviors from this data.
The Team
Our goal is to revolutionize the field of visual representation learning, enabling advanced robotic manipulation by developing sophisticated models that understand and interpret complex, dynamic environments. Our team has deep cross-functional expertise across computer vision, machine learning, robotics, and data science. We measure our success through significant advancements in visual perception capabilities, as well as impactful contributions to open-source projects and academic publications. Our guiding principle is the pursuit of cutting-edge technology that empowers robots to autonomously perform a wide array of tasks in varied and unstructured settings. We operate a fleet of robots and leverage large-scale visual datasets to train and refine our models, ensuring that they can robustly and efficiently function in real-world scenarios. Join us in our mission to push the boundaries of visual representation learning and transform robotic manipulation.
The Opportunity
Our Computer Vision (CV) team is looking for Computer Vision Research Scientists with expertise in Video Generation, Spatio-temporal Representation Learning, Vision-as-Inverse-Graphics (including Differentiable Rendering), or related fields, to improve dynamic scene understanding for robots! We are working on some of the hardest scientific challenges around the safe and effective usage of large robotic fleets, simulation, and prior knowledge (geometry, physics, domain knowledge, behavioral science), not only for automation but also for human augmentation.
As a Research Scientist, you will work with a team proposing, conducting, and transferring innovative research. You will use large amounts of sensory data and simulation to address open problems, publish at top academic venues, and test your ideas in the real world (including on our robots of course!). You will also work closely with other teams at TRI to transfer and ship our most successful algorithms and models towards world-scale long-term autonomy and advanced assistance systems.
Responsibilities
- Conduct high-reaching research that solves problems of high value and validates them in benchmarks and systems.
- Push the boundaries of knowledge and the state of the art in ML areas including simulation, perception, prediction, and planning for autonomous driving and robotics.
- Partner with a multidisciplinary team including other research scientists and engineers across the CV team, TRI, Toyota, and our university partners.
- Present results in verbal and written communications, internally, at top international venues, and via open-source contributions to the community.
- Lead collaborations with our external research partners (e.g., Stanford, Berkeley, MIT) and mentor research interns.
Qualifications
- PhD or equivalent years of experience in Machine Learning, Robotics, Computer Vision, or a related field.
- Deep expertise in at least one key ML area among Computer Vision, RL, ML theory, AI ethics.
- Consistent record of publishing at high-impact conferences/journals (CVPR, ICLR, NeurIPS, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.) on the aforementioned topics.
- Proficient at scientific python, Unix, and a common DL framework (preferably PyTorch). Experience with distributed learning (especially on AWS) is a plus.
- You can identify, propose, and lead new research projects, working in collaboration with other researchers and engineers to complete it from initial idea to working solution.
- You are intrigued by large-scale challenges in ML, especially in the space of Automated Driving, Robotics, and for societal good in general.
- You are a reliable teammate. You like to think big and go deeper. You care about openness and delivering with integrity.
The pay range for this position at commencement of employment is expected to be between $165,760 and $238,280/year for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave) and an annual cash bonus structure. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
