Intern, 3D Perception

As an Intern for 3D Perception at Mercedes-Benz Research & Development North America, you'll engage in developing machine learning methods focused on accurate 3D perception and reconstruction. This includes enhancing multi-sensor fusion techniques using LiDAR, cameras, and radar to improve environmental understanding. You'll also evaluate algorithms on real-world autonomous driving datasets and collaborate with the team for integration into the AD perception stack.

To qualify for the Intern, 3D Perception role at MBRDNA, candidates should have an MS degree or be pursuing a PhD in Computer Science, Electrical Engineering, Robotics, or a related field, with a focus on machine learning and computer vision. You should have experience in developing deep learning models, particularly for 3D scene understanding, and solid programming skills in Python, along with familiarity with libraries like PyTorch or TensorFlow.

Successful candidates for the Intern, 3D Perception position at Mercedes-Benz Research & Development North America should possess strong programming skills in Python. Familiarity with deep learning libraries such as PyTorch and TensorFlow is also crucial, as you'll be developing and training algorithms that advance our perception technologies.

While having experience is beneficial, especially in developing deep learning models and understanding concepts like SLAM, NeRF, and Gaussian Splatting, it's not strictly required for the Intern, 3D Perception position at MBRDNA. Your eagerness to learn and apply machine learning and computer vision techniques is what truly matters!

Interns at Mercedes-Benz Research & Development North America will receive hands-on experience in a leading automotive technology environment. While internships are separate from full-time benefits, you will enjoy valuable perks such as flexible working hours, a collaborative team atmosphere, and the opportunity to contribute to innovative projects in the automated driving space.

Discuss specific projects where you've applied machine learning to tackle 3D perception problems. Highlight any algorithms or frameworks used, your approach to handling datasets, and the outcomes of your implementations.

Elaborate on the importance of multi-sensor fusion in autonomous driving. Describe how different sensor types like LiDAR, cameras, and radar work together to enhance environmental understanding and the overall robustness of perception systems.

Explain your methodologies for diagnosing issues in machine learning models. Discuss tools you use for visualization, predictions, and performance assessment. Providing specific examples can demonstrate your hands-on experience.

Define each of these concepts—SLAM (Simultaneous Localization and Mapping), NeRF (Neural Radiance Fields), and Gaussian Splatting. Explain how they contribute to 3D perception in autonomous vehicles and give insights into possible applications.

Outline your strategies for facilitating clear communication among team members, such as using common terminologies, conducting regular check-ins, and leveraging collaborative tools, ensuring everyone stays aligned on objectives and progress.

Select a relevant project and discuss the challenges faced, focusing on both technical aspects and team dynamics. Illustrate how you approached problem-solving and what you learned from the experience.

Reflect on your goals for the internship, such as developing specific skills, gaining industry insights, and contributing to ongoing projects. Express your enthusiasm for learning and making a meaningful impact at MBRDNA.

Highlight your commitment to continuous learning by mentioning specific resources such as academic journals, online courses, workshops, or relevant conferences that you follow to keep up with industry trends.

Discuss your proficiency in programming languages like Python and any specific libraries suited for machine learning and computer vision. Mention your familiarity with tools used for data visualization and model evaluation.

Share your personal and professional motivations for pursuing a career in the automotive industry. Emphasize your passion for innovation, technology, and how autonomous driving fascinates you as a field with transformative potential.