Internship
Machine Learning – Perception Internship/Co-op
Confirmed live in the last 24 hours
Teleo
1-10 employees
Retrofitting heavy equipment for remote control
Compensation Overview
$28.85 - $34.62Hourly
Palo Alto, CA, USA
Position requires onsite presence in Palo Alto, CA.
- 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.
- 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.
- 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.
Teleo transforms heavy equipment in the mining and construction sectors into remotely controlled robots. By retrofitting existing machinery with advanced technology, operators can control equipment from a safe location, typically an office, which significantly enhances crew safety by keeping them away from hazardous environments. The company focuses on clients in industries that rely heavily on heavy machinery and face safety challenges. Unlike competitors that sell new machinery, Teleo's business model allows clients to upgrade their current fleets without the high costs of new equipment. Revenue is generated through the sale and installation of retrofit technology, along with ongoing maintenance and support services. By enabling operators to control multiple machines from one location, Teleo improves both safety and operational efficiency, making its solutions appealing to its target market.
Company Stage
Series A
Total Funding
$35.3M
Headquarters
Palo Alto, California
Founded
2019
Simplify's Take
What believers are saying
- Teleo raised $16.2M to expand into new industries and enhance AI capabilities.
- Teleo's dealer network expansion indicates growing demand in the Midwest and Asia-Pacific.
- Teleoperation technology is gaining traction due to labor shortages in construction.
What critics are saying
- Competition from Built Robotics and SafeAI could impact Teleo's market share.
- Regulatory changes in mining and construction could pose compliance challenges.
- Economic downturns in construction and mining may reduce demand for Teleo's technology.
What makes Teleo unique
- Teleo retrofits existing machinery, avoiding high costs of new equipment purchases.
- Teleo enhances safety by enabling remote operation of heavy machinery.
- Teleo's technology allows operators to control multiple machines from a single location.
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