About us:
Aeva’s mission is to bring the next wave of perception to a broad range of applications from automated driving to industrial robotics, consumer electronics, consumer health, security, and beyond. Aeva is transforming autonomy with its groundbreaking sensing and perception technology that integrates all key LiDAR components onto a silicon photonics chip in a compact module. Aeva 4D LiDAR sensors uniquely detect instant velocity in addition to 3D position, allowing autonomous devices like vehicles and robots to make more intelligent and safe decisions.
Role overview:
We are looking for a Senior Localization Engineer in our CLAMS (calibration, localization, and mapping) team. You will be working on implementing SOTA methods in state estimation, optimizing, and deploying Aeva’s 4D FMCW LiDAR algorithms to production and push autonomous driving performance.
What you'll do:
Contribute to Aeva’s 4D state estimation stack that will be deployed in production
Ability to quickly prototype novel algorithms, implement them, and iterate fast
Ensure code is optimized for performance and scalability
Adhere to coding standards and best practices to ensure consistency and quality in all code
Take ownership of assigned tasks and ensure timely and accurate completion with documentation and tests
What you'll have:
5+ years of experience with demonstrated ability to create and deploy real-time state estimation or SLAM systems
Have a MS or PhD in a relevant program such as Robotics, Computer Science, Electrical Engineering, or similar
Experience with techniques such as LIO, Kalman Filtering, Bayesian Methods, and Sensor Fusion (with LiDAR/IMU/GNSS)
Experience with 3D data and representations (point clouds, meshes, etc.)
Strong fundamentals of linear algebra and 3D geometry
Highly skilled in C++ development and experience with the Linux environment
Skilled in scripting languages such as Python and Bash
Nice to haves:
Knowledge of working principles for RADARs or LiDARs
Experience with online extrinsic calibration methods
Experience with robotics or autonomous vehicle software frameworks such as ROS/ROS2 or similar
Experience with modern build systems such as Bazel or similar
Experience with run-time optimization techniques (e.g. parallelization, vectorization, cache-friendly development)
