Software Engineer Intern- Simulation

As a Software Engineer Intern - Simulation at Plus, your responsibilities will primarily revolve around designing and developing data-driven methods for generating realistic and challenging edge-case scenarios for autonomous vehicle testing. You will analyze the fidelity, diversity, and coverage of these scenarios against actual driving data using various statistical metrics. Additionally, collaborating with cross-disciplinary teams to enhance scenario generation algorithms and implementing smart agent models will be essential parts of your role.

To qualify for the Software Engineer Intern - Simulation position at Plus, you should be pursuing an MS or PhD in a related field such as mechanical, electrical, or aerospace engineering, physics, or computer science. A strong understanding of domain randomization and statistical methods, along with familiarity in autonomous vehicle simulation and robotics concepts, are critical. Experience in prediction, planning, and control within simulation tools will be highly advantageous.

The Software Engineer Intern - Simulation at Plus should possess a robust skill set in deep learning, statistical sampling, and vehicle behavior modeling. A strong grasp of probabilistic methods is crucial, along with experience in developing simulation tools for autonomous vehicles. Additionally, excellent communication skills and the ability to collaborate effectively in a team environment will help you excel in this innovative role.

The hourly wage for a Software Engineer Intern - Simulation at Plus ranges from $19 to $65 an hour, depending on your qualifications and experiences. Plus is committed to providing a highly competitive salary along with a comprehensive benefits package that includes 401(k) plans, making this an attractive opportunity for aspiring engineers.

Working as a Software Engineer Intern at Plus immerses you in a highly future-oriented and innovative environment. You will not only gain hands-on experience in advanced technologies but also have ample opportunities for personal and professional development. Plus values learning, offering resources to hone your skills and advance your career in the dynamic field of autonomous driving technology.

In answering this question, detail the project's scope, the specific deep learning techniques you used, and the outcomes achieved. Highlight any challenges faced and how you overcame them, as well as the impact your work had on the overall project, connecting to the value it can bring to Plus.

Discuss various statistical metrics and domain-specific criteria you would utilize to analyze the fidelity and coverage of generated scenarios against real-world driving data. Emphasize your understanding of simulation-based verification techniques to convey your critical thinking skills.

Share examples of your collaborative experiences, focusing on communication strategies, conflict resolution, and how you contributed to team objectives. Relate this to working at Plus, where cross-disciplinary collaboration is vital for innovation.

Provide insights into your education or hands-on experience with probabilistic models. Discuss how these methods can enhance the realism and reliability of edge-case scenarios at Plus.

Mention specific simulation tools and languages you've worked with, such as Gazebo, CARLA, or ROS. Discuss how your familiarity with these tools aligns with the responsibilities of a Software Engineer Intern at Plus.

Demonstrate your awareness of current industry challenges, such as dealing with the complexity of real-world scenarios. Discuss solutions or approaches that you believe could help address these challenges, showcasing your analytic and problem-solving skills.

Outline your strategies for incorporating a variety of edge cases in your simulation work. Discuss techniques like domain randomization and statistical sampling to create robust testing environments that ensure coverage.

Provide a clear definition of domain randomization and discuss its relevance in generating diverse training scenarios for deep learning models on autonomous vehicles. Connect this back to its application in your potential work at Plus.

Discuss your methods for keeping current, such as attending industry conferences, following relevant publications, or participating in online forums. Share how this knowledge can benefit your role at Plus.

Articulate your motivations for choosing Plus, focusing on its innovative approach to autonomous driving, the opportunity for personal growth, and your desire to contribute to shaping future technologies. Show genuine enthusiasm for the company’s mission.