Collision Avoidance System, Machine Learning Internship/Co-op

1 Month ago • Upto 1 Years • Artificial Intelligence

About the job

Job Description

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As an Autonomous Vehicle Perception Intern, you will play a crucial role in the design and implementation of deep neural networks that integrate data from various sensor types to enhance the perception and predictive capabilities of autonomous vehicles in challenging urban environments. This internship provides an exciting opportunity to work alongside experts in the field and gain valuable experience in modern deep-learning techniques.

The candidate will have the opportunity to:
1. Collaborate with our team of engineers to develop and implement state-of-the-art deep neural networks tailored for autonomous vehicle perception.
2. Work with sensor data from various sources, such as LiDAR, radar, and camera, to create robust models that improve the vehicle's ability to perceive and predict its surroundings.
3. Contribute to the development and enhancement of a product-ready code base, ensuring that code is scalable, maintainable, and meets high-quality standards.

Technical Qualifications & Language Requirements

    • Experience with modern deep learning frameworks (e.g., Pytorch and Tensorflow)
    • Fluency in C++ 
    • Experience in implementing and training deep learning models
    • Experience in computer vision is nice to have
    • MSE degree or a senior PhD candidate in Computer Science, Computer Vision, Robotics or related fields
Compensation
The monthly salary range for this position is $6,500 to $9,500. Compensation will vary based on role, degree level and type, and benefits will be offered based on eligibility. Additional benefits may include medical insurance, 401k, and a housing stipend.

About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.


Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
Compensation
The monthly salary range for this position is $6,500 to $9,500. Compensation will vary based on role, degree level and type, and benefits will be offered based on eligibility. Additional benefits may include medical insurance, 401k, and a housing stipend.

About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.


Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
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About The Company

Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.

Seattle, Washington, United States (On-Site)

Foster City, California, United States (On-Site)

Foster City, California, United States (On-Site)

Foster City, California, United States (On-Site)

Foster City, California, United States (On-Site)

Foster City, California, United States (On-Site)

Foster City, California, United States (On-Site)

San Diego, California, United States (Hybrid)

Foster City, California, United States (Hybrid)

Foster City, California, United States (On-Site)

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