Machine Learning Perception Internship / Co-op, Teleo
Winter / Spring 2025
Office located in Palo Alto, CA
Autonomous construction robotics
Open for applications
Autonomous construction robotics
21-100 employees
Open for applications
Office located in Palo Alto, CA
21-100 employees
Company mission
Teleo's mission is to revolutionize how we build the world.
Role
Who you are
- 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
Desirable
- 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
What the job involves
- The 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
- 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
Our take
Operating a massive piece of heavy equipment like a bullddozer for 8-10 hours a day is a challenging job. It's tiring, unsafe and requires a great deal of synchronisation with other workers and vehicles on the job. Teleo is lightening this burden for construction teams with remote and autonomous control of heavy equipment.
The startup has pursued a pragmatic “crawl-walk-run” approach to deliver the benefits of supervised autonomy now. Instead of having each machine in a fleet operated by a driver in a cab, they’re all being controlled remotely by a single human operator miles away from the job site.
The hope is that the technology matures toward fully autonomous heavy equipment operation. Like any new, next-generation technology, it can take some getting used to. However construction workers are simply adapting to robots on site as a another tool to get the job done, putting Teleo in a strong position as it sets out to disrupt the construction industry.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Jun 2022
$12m
SERIES A
Dec 2021
$7.9m
EARLY VC
Total funding: $20.1m
Company HQ
Ventura, Palo Alto, CA
Articles
Leadership
Rom Clement
(CTO & Co-Founder)Previously Head of hardware & Technology Strategist at Lyft, working in self-driving. Before that, worked as a Senior Engineering Manager at Google in Google Maps. At Google Fiber, they grew a team responsible for the development of laser telecommunication systems for space and aerial applications. Rom has a master’s degree in aerospace engineering from the University of Michigan.
Vinay Shet
(CEO & Co-Founder)Prior to Teleo, they were the Director of Product Management at Lyft working on building Lyft's self-driving cars. Prior to Lyft, Vinay led Product Management at Google Street View, Google Maps, and Google reCAPTCHA launching several consumer products used by millions of users worldwide. Vinay has a Ph.D. in Computer Science, focusing on Computer Vision from the University of Maryland.
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