Basic Introduction on how to become a Self-driving Car Engineer

by October 20, 2020 0 comments

Self-driving Car

With rapid demand for autonomous vehicles, careers in this sector are up ticking too

We all know that connected autonomous or self-driving cars are going to hit market roads soon. Meanwhile, the path toward these vehicles has proven costlier and far more complicated. So we need to look for more brilliant minds who can help propel this sector with innovative ideas. In the coming years, we shall witness a sharp growth in the sector’s job opportunities, especially for the hardware and software engineers looking to work on self-driving car technologies. This is because the technology demands a high degree of complexity requiring quality software engineering and great organization. These two things may fall short when trying to push forward in the highly competitive field of self-driving.

Further huge investments in this sector may attract enormous opportunities for engineers. The skills needed for self-driving car engineering jobs include artificial intelligence (AI), computer science, and robotic sensor systems. Further, this branch has its own challenges and thrills too. For instance, the autonomous car must be designed so that the risk of adverse consequences is minimized.


Why Do we Need Self-driving Car Engineer?

A self-driving car engineer is a specialized software engineer, and one of the core responsibilities for this role is to ensure a high level of software quality. As this concept is becoming a reality, the responsibility and expectations from a self-driving car engineer rises too. In today’s market scenario high software refers to well-defined and consistent software architecture, embedded software development, proper test coverage like unit tests, smoke tests, and integration tests for every build and more. Moreover, as driverless vehicles become more widespread, it will be become necessary to implement a quality road system and engineering expertise is the key to making that happen. According to Paysa, an informational website for employees to make educated, informed career decisions, the average market salary for self-driving car engineers is currently US$233K per year, which includes a base salary of US$138K, a US$26.1K annual bonus, US$21K signing bonus and US$73.5K annual equity.


How to Get Started?

Students need to get proficient in mathematics at the elementary and high school levels and then continue with advanced college courses like linear algebra and calculus. They should also be learning coding in C, C++, and Python. Apart from that, interested students can join the Robotics Club. Generally, a self-driving car is like a robot, so getting experience working with these machines will be invaluable in the job market. Robotics teams include builders and coders—and promoters—so they offer a kind of industry preview. Next, they can take up basic and advanced courses in artificial intelligence, computer vision, machine learning and SLAM techniques (simultaneous localization and mapping), which depends on probability and statistics. They can also learn about time-series prediction, Databases: relational and NoSQL, sensor technology: camera, lidar, radar, ultrasonic, vehicle kinematics, SD, and HD Maps. Plus have hands-on practice in simulation and real-time computer graphics, real-time processing, parallel computing, optimization, along with sound knowledge in functional safety.


Advanced Courses

Currently, Udacity offers a self-driving car engineer nanodegree. Even Udemy (The Complete Self-Driving Car Course – Applied Deep Learning) and Coursera ( State Estimation and Localization course,  Self-Driving Car specialization,  have similar products. The Udacity program is held at 15 hours a week, taking six months to complete, and was built in partnership with companies like Mercedes-Benz, Uber, and BMW. Topics covered include Deep Learning, Sensor Fusion, and System Integration, all from the comfort of your own home.  If someone is interested in a more academic approach, MIT has videos and slides from its “Deep Learning for Self-Driving Cars” coursework.

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