Machine Learning Intern, Natural Language & Robot Learning

Los Altos, CA

Applications have closed

Toyota Research Institute

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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 Human-Centered AI, Human Interactive Driving, Energy and Materials, Machine Learning, and Robotics.
This is a Summer 2023 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.
Team
Our Machine Learning (ML) team is looking for Research Interns for the Summer of 2023 with a focus on Natural Language Processing, Computer Vision and Multi-Modal Foundation Models. We are aspiring to make progress on some of the hardest scientific challenges around the safe and effective usage of large robotic fleets, simulation, and prior knowledge (physics, domain knowledge, behavioral science), not only for automation but also for human augmentation.
About the Internship
As a Research Intern, you will work with a multidisciplinary team proposing, conducting, and transferring pioneering research in Machine Learning. You will use large amounts of sensory data and simulation to solve open problems, work towards publications at top academic venues  and test your ideas in the real world (including on our robots (https://www.tri.global/news/virtual-robotics-event/) of course!).

Responsibilities

  • Conduct daring research primarily in Natural Language Processing, Computer Vision and Robotics, but also in Planning and Dialog that solves open problems of high practical and/or ethical value and validate it in real-world benchmarks and systems.
  • Push the boundaries of knowledge and the state of the art in areas including language and vision for robotics and embodied foundation models.
  • Partner with a multidisciplinary team including other research scientists and engineers across the Machine Learning team.
  • Stay up to date on the state-of-the-art in Machine Learning ideas.
  • Present results in verbal and written communications at international conferences, internally, and via open-source contributions to the community.
  • Bachelor’s or Master’s degree in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering), especially in Natural Language Processing, Machine Learning, Robotics, Control Theory, Computer Vision, or related fields preferred.
  • Expertise in at least one key ML area.

Qualifications

  • Publication or desire to publish at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, UAI, RSS, ICRA, COLT, CDC, L4DC, CVPR, ICCV, ECCV, PAMI, IJCV, EMNLP, ACL, NAACL etc.) on some of the aforementioned topics.
  • Proficiency with one or more coding languages and systems, preferably python, Unix, and a Deep Learning framework (e.g., PyTorch).
  • Can execute on research projects, working in collaboration with other members of the Machine Learning team. 
  • Passionate about machine learning research.
  • A reliable teammate who loves to think big, go deeper and can deliver with integrity.
Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
TRI provides Equal Employment Opportunity without regard to the 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.

Tags: Computer Science Computer Vision Deep Learning EMNLP Engineering ICLR ICML Machine Learning Mathematics NeurIPS NLP Physics Privacy Python PyTorch Research Robotics

Perks/benefits: Conferences

Region: North America
Country: United States
Job stats:  81  15  0

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