About the job
About Us
Nuro is a pioneering self-driving technology firm focused on democratizing autonomy for everyone. Established in 2016, we are on a mission to create the world's most scalable autonomous driver. Our innovative approach blends advanced AI with automotive-grade hardware, allowing us to license our core technology, the Nuro Driver™, across diverse applications including robotaxis, commercial fleets, and personal vehicles. Our proven technology, tested through numerous self-driving deployments, provides automakers and mobility platforms with a clear path to commercial-scale autonomous vehicles, fostering a safer, more connected future.
Position Overview
We are excited to expand our robotics team and are seeking a talented Senior Software Engineer to join our Sensor Data and Calibration unit. The ideal candidate will possess a strong background in robotics and machine learning, with a focus on developing sophisticated synthetic sensor simulation models and algorithms. Experience in research, development, and application of machine learning techniques (such as NeRF or Gaussian splatting) for generating synthetic sensor data, including photorealistic images and realistic LiDAR or radar outputs, is essential.
Key Responsibilities
- Research and create cutting-edge synthetic sensor simulation methodologies.
- Evaluate and characterize the realism and effectiveness of synthetic sensor data.
- Address essential inquiries regarding sensor data and autonomous performance.
- Collaborate with various teams across autonomy, infrastructure, and systems to define mapping requirements.
Qualifications
- One of the following:
- PhD in machine learning, computer science, electrical engineering, robotics, or a related field, with 3+ years of industry experience.
- Master's degree with 4+ years of industry experience.
- 5+ years of industry experience.
- In-depth knowledge of machine learning fundamentals with practical experience in training and assessing contemporary ML models.
- Proficient in Python, with experience in deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Preferred Qualifications
- Strong grasp of 3D geometry and state estimation principles.
- Experience in systems-level coding.
- Familiarity with simulating and modeling real sensors (camera, LiDAR, radar, IMU, etc.), including noise modeling.
- Expertise in modern ML graphics techniques, such as NeRF, Gaussian Splatting, and/or generative models.

