Machine Learning - Perception Internship/Co-op (Summar/Fall 2025)

Teleo is a robotics startup disrupting a trillion-dollar industry. Teleo converts construction heavy equipment, like loaders, dozers, excavators, trucks, etc. into autonomous robots. This technology allows a single operator to efficiently control multiple machines simultaneously, delivering substantial benefits to our customers while significantly enhancing operator safety and comfort.Teleo is founded by Vinay Shet and Rom Clément, experienced technology executives who led the development of Lyft’s Self Driving Car and Google Street View. Teleo is backed by YCombinator, Up Partners, F-Prime Capital, and a host of industry luminaries. Teleo’s product is already deployed on several continents and generating revenue. Teleo is poised for rapid growth. This presents a unique opportunity to be part of a team that is creating a product with a profound impact on our customers, working on cutting-edge 100,000-pound autonomous robots, engineering intricate systems at the intersection of hardware, software, and AI, and joining the early stages of an exciting startup journey.About the RoleThe ML Perception role at Teleo is responsible for developing machine learning-based methods to understand and interpret scenes using various sensor modalities. This critical information enables our path-planning systems to safely navigate and avoid obstacles.

Responsibilities

• Work with the ML team to improve existing as well as implement new perception features within our systems. 
• Stay abreast of the latest research by reading and implementing state-of-the-art methods from academic papers.
• Regularly communicate progress, challenges, and achievements to the team.
• Contribute to the advancement of the field by publishing research papers and filing patents.

Minimum Qualifications

• Ongoing/completed Ph.D. or Master’s degree in Computer Science or a related field. Bachelor’s degree in Computer Science or a related field with exceptional skills can be considered as well.
• Proficiency in Python and PyTorch.
• Solid understanding of neural networks and machine learning fundamentals.
• Experience with a vision-based deep learning project.
• Strong enthusiasm for continuous learning, including reading academic papers and participating in discussions about current trends in computer vision.

Preferred Qualifications

• Experience with perception projects involving cameras and/or lidar for tasks such as object detection, scene segmentation, depth estimation, freespace estimation, etc.
• Experience with Vision-Language Models (VLMs) and/or Large Language Models (LLMs).
• Good understanding of calibrating fisheye cameras using advanced models like the double sphere camera model.
• Proficiency in C++.
• Experience with version control systems, particularly Git.
• Authorship or co-authorship of papers presented at conferences like CVPR, NeurIPS, IROS, etc.
• Self-motivated and capable of planning and completing tasks independently.