Perception Tracking Engineer • Mid-Level

Who you are

You have experience in designing algorithms related to tracking, filtering, and state management — you can approach perception results not just as frame-level outputs but as temporal challenges that require innovative solutions. Your ability to implement and optimize algorithm ideas in real-time C++ systems sets you apart, and you understand the importance of stability in both environmental and object representations.

Your problem-solving skills allow you to structurally analyze and improve the causes of instability such as flicker and discontinuity — you thrive on challenges that require a deep understanding of temporal consistency and the dynamics of ego-motion. You hold at least a Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or a related field, with a preference for candidates with a Master's degree.

You have a solid background in developing perception systems for autonomous driving or Advanced Driver Assistance Systems (ADAS) — your experience includes performance analysis and optimization in real-time systems, as well as building automated evaluation pipelines for large-scale log analysis.

What you'll do

In this role, you will be responsible for designing and implementing temporal tracking and modeling logic for frame-level results generated by perception modules. You will develop algorithms to mitigate discontinuities, flicker, and false appearances or disappearances in environmental representations, ensuring that lane markings, traffic light states, and occupancy data are consistently represented over time.

You will structure various sensor-based perception results into stable forms that can be directly utilized for driving decisions and control functions — your work will involve maintaining and updating representations of lane markings, traffic light positions, and object states in a temporally and spatially continuous manner. You will define and manage outputs that include state, confidence, and persistence, ensuring that they meet real-time implementation and performance optimization criteria.

Your responsibilities will also include performance evaluation and tooling, where you will define quality metrics to quantify temporal stability, continuity, and consistency. You will develop tools for large-scale log-based performance and quality analysis using C++ and Python, and build regression testing and automated evaluation pipelines to ensure the reliability of your implementations.

What we offer

At 42dot, you will be part of a team that is at the forefront of autonomous driving technology — we offer a collaborative environment where innovation is encouraged, and your contributions will directly impact the future of mobility. You will have opportunities for professional growth and development, working alongside experts in the field.

We provide competitive compensation and benefits, along with a supportive workplace culture that values diversity and inclusion. Join us in our mission to create safer and more efficient autonomous driving systems.