Robotics Camera Engineer

As a Robotics Camera Engineer at Applied Intuition, your primary responsibilities include developing and maintaining Linux kernel drivers for camera systems, focusing on MIPI CSI-2 cameras used on ARM SoCs. You’ll also design V4L2-compliant drivers, create video nodes for platforms like NVIDIA Jetpack, and collaborate with multidisciplinary teams to advance camera system software. Documenting your work and contributing to process improvements will also be crucial, empowering the team to enhance efficiency.

To be considered for the Robotics Camera Engineer role at Applied Intuition, candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Key qualifications include strong experience in Linux kernel driver development, proficiency in C or C++, familiarity with V4L2 frameworks, and an understanding of embedded systems architecture. Nice-to-have skills include work with device trees, kernel debugging, and camera firmware understanding.

Compensation for the Robotics Camera Engineer position at Applied Intuition includes base salary, equity, and a comprehensive benefits package. The salary range for this role is between $94,000 and $264,000 USD annually, which may vary based on several factors, including experience, credentials, and interview performance. Additionally, employees enjoy perks such as health insurance, retirement benefits, wellness stipends, and paid time off, contributing to a well-rounded total compensation package.

Applied Intuition primarily operates as an in-office company, with the expectation that employees, including Robotics Camera Engineers, will work from the office five days a week. However, the company also recognizes the importance of flexibility, allowing for occasional remote work, early departures for personal obligations, and starting the day with remote meetings, ensuring a healthy work-life balance.

As a Robotics Camera Engineer at Applied Intuition, you can expect to engage in exciting projects focused on advanced camera systems, integrating embedded vision technologies into AI-driven machines. You'll work on enhancing Linux kernel drivers, developing innovative applications for various industries, and collaborating closely with cross-functional teams to deliver next-generation automotive solutions that our customers, including 18 of the top 20 global automakers, rely on.

When responding to this question, highlight specific projects where you developed or maintained Linux kernel drivers. Discuss the challenges you faced, the frameworks you worked with (like V4L2), and how your contributions improved functionality or performance.

In answering this question, describe your systematic approach to troubleshooting, from analyzing logs and using debugging tools to isolating the problem. Provide a specific example where you successfully resolved an issue and what tools or methods you utilized.

Discuss your understanding of the MIPI CSI-2 protocol, and provide examples of how you've implemented it in projects. Highlight your practical experience in linking camera hardware with software, emphasizing your role in addressing any interoperability challenges.

Emphasize the importance of comprehensive documentation in your workflow. Discuss your approach to documenting code, design decisions, and procedures to ensure that knowledge is shared within the team. Provide examples of documentation tools you have used.

Share your extensive experience utilizing Git for version control, detailing your knowledge of branching, merging, and collaboration with team members. Discuss specific projects where your use of Git facilitated smoother workflows or resolved conflicts.

Here, provide a narrative that illustrates your collaboration skills. Describe a project involving engineers, project managers, and possibly other stakeholders, emphasizing your contributions and how you facilitated communication among teams to achieve common goals.

Highlight the best practices you adhere to while designing camera drivers, such as adhering to coding standards, focusing on modular design for maintainability, and performing thorough testing of drivers. Discuss the importance of adhering to compliance with industry standards like V4L2.

Mention your methods for staying current, whether through attending industry conferences, joining online forums, or engaging with professional academic journals. Explain how you incorporate new findings into your work and the impact those advancements have had on your previous projects.

In your answer, discuss a specific challenge you encountered while working with embedded systems and how you addressed it. This might include dealing with resource constraints, real-time processing challenges, or the integration of various hardware components.

Use this question to express your passion for the field and how Applied Intuition’s mission aligns with your career goals. Discuss your enthusiasm for working with advanced technologies and the unique opportunity to contribute to safety and efficiency in AI-driven machines.