Have you ever wondered what it takes to work in the field of self-driving cars?
An interview with Jérémy Cohen, founder and CEO of Think Autonomous, a great platform to learn self-driving and advanced computer vision skills. In this interview, we dive into the self-driving car industry and different ML-related roles.
In this interview, we discuss getting into the industry and trying to demystify some myths. Here are some teasing questions we discuss:
- How can one become a self-driving car engineer?
- What are LiDARs, and how do they work?
- What do you think about using LiDAR vs. cameras on self-driving cars?
- Do you think a $200 000 salary for a computer vision engineer is a myth?
Here are a few extra insights for getting into the self-driving car industry to help you decide if it’s worth a listen:
- Establish a strong engineering background. Consider obtaining an engineering degree or pursuing a relevant master’s program before transitioning into your desired field.
- Learn as much as you can online. Take advantage of online resources such as courses and communities to develop your skills and connect with others in the field.
- Be strategic about building your portfolio. Start with essential courses and skills, such as computer vision, before diving into more specialized areas like self-driving cars.
- Don’t settle for a low salary or an uninteresting job. While it’s important to pursue your dream job, it’s also okay to make it a long-term goal and gradually improve your skills along the way.
We hope you enjoy this episode!
Let me know your thoughts in the comments and if you’d like more episodes with Jérémy in the self-driving car industry! (or listen to the podcast on the streaming platforms)
FAQ
What does a self-driving car engineer work on?
Roles span perception, prediction, planning, control, simulation, mapping, data, infrastructure, and safety validation.
Which skills are useful for autonomous-driving ML?
Computer vision, machine learning, robotics, Python or C++, geometry, data analysis, and software engineering are common.
What does the Jérémy Cohen interview cover?
It explains the industry, different ML roles, learning paths, and what self-driving work looks like in practice.
Do all autonomous-driving roles require the same background?
No. Research, embedded systems, simulation, data, and production engineering emphasize different combinations of skills.
How can a beginner prepare for this field?
Build projects around perception or robotics, learn the system fundamentals, and document how you evaluated failures.