Perception Software Engineer - (Remote - US) - job 2 of 2

As a Perception Software Engineer at Jobgether, your main responsibilities include designing and implementing real-time multimodal perception models, fine-tuning deep learning models for embedded hardware like Jetson, and leading research in sensor fusion and scene understanding. You will also be responsible for documenting and sharing your findings both internally and externally, which could contribute to publications.

To apply for the Perception Software Engineer position at Jobgether, you need a Bachelor’s degree in Computer Science, Electrical Engineering, or a related field and at least three years of experience in machine learning, preferably in autonomous driving sectors. Familiarity with programming languages like Python and C++, as well as deep learning frameworks such as PyTorch, is essential.

Jobgether fosters a collaborative and mission-driven environment where Perception Software Engineers can grow. Employees are encouraged to engage in R&D projects, collaborate on challenging problems, and share insights through documentation and presentations, contributing both to their personal development and to the team's collective knowledge.

A Perception Software Engineer at Jobgether will work on projects related to autonomous mobility, including developing sophisticated perception systems that fuse data from various sensors. These projects will have a direct impact on next-generation transportation solutions and urban transit enhancements, emphasizing real-time inference and anomaly detection in real-world applications.

The work culture for Perception Software Engineers at Jobgether is inclusive and supportive, valuing diverse backgrounds and perspectives. The team environment encourages collaboration and the exchange of ideas, allowing engineers to thrive on cutting-edge technology projects while enjoying a flexible work setup.

In your response, detail a systematic approach that covers defining the objectives, selecting appropriate sensors, and developing algorithms for data fusion. Emphasize the importance of robustness and efficiency in the system to ensure effective real-world performance.

Highlight specific projects where you utilized PyTorch, explaining the models you built, challenges you faced, and how you optimized their performance. Emphasize your understanding of deep learning architectures and your ability to implement them using this framework.

Discuss strategies such as model pruning, quantization, and architecture search you have employed in previous projects. Cite examples where these strategies allowed you to effectively deploy models on platforms like Jetson.

Share specific instances where you worked on projects involving the integration of data from different sensors, such as cameras, lidar, and radar. Describe how you dealt with challenges like synchronization and data quality.

Discuss various techniques you are familiar with, such as statistical methods, machine learning approaches, or neural networks. Provide examples of any projects where you implemented these methods successfully.

Outline your experience with data preparation and management in interdisciplinary settings. Discuss the importance of labeling, cleaning data, and ensuring compatibility among various modalities in your work.

Choose a specific project, describe the problem in detail, the approach you took, the tools and techniques you used, and how you ultimately resolved it, demonstrating your problem-solving skills and technical expertise.

Emphasize the importance of clear and effective communication in ensuring that all team members are aligned on project goals, progress, and challenges. Highlight any tools or practices you use to facilitate good communication.

Discuss your commitment to continuous learning. Mention specific resources you follow, such as journals, conferences, or online courses, highlighting how you apply what you learn in your work.

Express your enthusiasm for the role and how your interests align with Jobgether's mission. Highlight your excitement about working on innovative technology in autonomous mobility and contributing to impactful projects.