Research Engineer - New Grad

As a Research Engineer - New Grad at Applied Intuition, your primary responsibilities will include collaborating with teams focused on end-to-end algorithms, deploying data-driven generation tools, conducting research on autonomous systems, and working alongside experienced research scientists to publish high-quality research. Your contributions will directly impact the development and efficiency of our autonomy stacks.

For the Research Engineer - New Grad position at Applied Intuition, candidates should ideally possess experience in areas like multi-view perception, 3D reconstruction, and behavior generation. A strong background in machine learning, computer vision, and autonomy is also preferred. While an MSc or PhD in a related field enhances your application, candidates with varying experiences are still encouraged to apply.

The Research Engineer - New Grad role at Applied Intuition is integral to improving our AI and autonomous technology. Your research efforts will support the development of customer-driven tools and systems which improve safety and efficiency in vehicle autonomy, thereby advancing the overall mission of creating intelligent machines that transform industries.

At Applied Intuition, the culture for Research Engineers is rooted in collaboration and innovation. Team members work in a fast-paced environment that fosters continuous learning and encourages sharing of best practices. You'll engage in exciting research while enjoying the support of a friendly team eager to make a significant impact in the automotive industry.

Research Engineers at Applied Intuition can expect an array of training and development opportunities, including collaboration with experienced scientists, involvement in high-profile research projects, and attendance at top-tier conferences. The company values continuous learning, which is evident in its supportive environment and dedication to employee growth.

In your response, provide specific examples where you've been involved in end-to-end autonomy projects. Discuss the methodologies you used and any tools or technologies that were integral to your work. Demonstrate your understanding of the challenges in implementing autonomy and how you tackled them.

When answering this question, emphasize aspects such as safety, robustness, real-time processing requirements, and integration with existing systems. It's crucial to consider the reliability of your algorithms under diverse driving conditions and their effectiveness in decision-making.

Share your methodology for conducting research, including defining objectives, gathering large-scale data, and leveraging statistical techniques or machine learning frameworks. Illustrate how your findings have been applied to solve real problems in past projects.

Discuss a noteworthy project, detailing your role, the challenges you faced, and the impact of your work. Be sure to highlight the steps taken to ensure accuracy and efficiency in the reconstruction process and how you collaborated with others during development.

Detail your familiarity with techniques such as reinforcement learning, imitation learning, and any specific algorithms you've employed. Provide an example of a successful implementation and the results you achieved to demonstrate your practical expertise.

Explain your approach to testing and validating algorithms, including the use of simulations, stress testing, and iterative improvements. Discuss methodologies for gathering feedback and how that influences the refinement of algorithm performance.

Emphasize the importance of interdisciplinary teamwork in advancing research initiatives. Provide examples of how you've collaborated with others, shared knowledge, and leveraged diverse expertise to enhance project outcomes.

Detail a specific problem, your investigative process, and the solutions you implemented to resolve the challenge. Highlight the skills you utilized and what you learned from the experience.

Share your passion for developing innovative solutions that make a real-world impact. Discuss any personal experiences or influences that have fueled your interest in the autonomy field and how they align with Applied Intuition's goals.

Mention the resources you utilize, such as academic journals, conferences, webinars, and networking with professionals in the field. Describe how you apply what you learn to your work to stay at the forefront of technology advancements.