Perception Engineer

A Perception Engineer at EpiSci is responsible for developing and integrating real-time sensor software solutions across various autonomous vehicles. They work on enhancing AI/ML algorithms, designing sensor controllers, and ensuring seamless deployment in real-world scenarios, collaborating closely with teams and customers.

To qualify as a Perception Engineer at EpiSci, candidates should possess a Master's or PhD in Electrical Engineering, Computer Science, or related fields, or have 5+ years of relevant experience. Proficiency with multiple sensor modalities and experience in deploying ML algorithms are essential.

As a Perception Engineer at EpiSci, you will work with advanced sensor technologies like EO, IR, radar, and acoustics, while utilizing programming languages such as Python and C++, and tools like Docker, embedded Linux, and machine learning frameworks including PyTorch and TensorFlow.

EpiSci promotes a flexible work environment but primarily requires employees to be in-office five days a week. However, they understand the importance of work-life balance and allow for occasional remote work as needed.

The Perception Engineer at EpiSci should be prepared for occasional travel, approximately every one to two months, for software and hardware integration as well as demonstrations, with travel averaging around 10-20% of the time.

Focus on specific projects where you deployed ML algorithms. Describe your methodologies, tools used, and the impact on outcomes. Be sure to relate your experience back to how it aligns with EpiSci’s needs in sensor software solutions.

Discuss the process of combining sensory data to produce more accurate and reliable information. Provide examples of techniques used, such as Kalman filters, and how these can be applied in the context of EpiSci's autonomous systems.

Explain your methodology for testing, including simulation tools and integration processes. Highlight how thorough validation ensures reliability in mission-critical applications for EpiSci’s projects.

Share specific projects or challenges encountered while programming in these languages. Relate your experience to integration efforts with sensor platforms and relevant technical details important for EpiSci's technology.

Discuss how you have engaged with HIL setups to test embedded systems. Give specific examples and highlight any special tools or methods you’re familiar with that would be relevant to EpiSci's operations.

Mention resources such as journals, webinars, or conferences that inform your practice. Emphasize your commitment to lifelong learning and how you can contribute to EpiSci’s innovative culture.

Provide a specific example of a challenge related to sensor integration or algorithm performance. Discuss your approach to problem-solving and how it aligns with EpiSci's mission in autonomy.

Express your view on constructive feedback as a tool for growth. Share examples of how you incorporated feedback to improve processes or deliverables in previous roles.

Highlight your communication strategies, tools you use for collaborative work, and past experiences that demonstrate your ability to work effectively with various stakeholders, especially relevant to EpiSci’s multi-team environment.

Provide a brief explanation of your experience using Docker for deploying applications, settings, and how it can streamline processes specifically in the context of EpiSci's projects and enhancing development efficiency.