Senior/Staff Machine Learning Engineer, Sensor Simulation

The Robot Age; Mountain View (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Nuro is hiring a senior or staff ML engineer to build synthetic sensor simulation for autonomous driving. The role focuses on generating realistic camera, lidar, or radar data and measuring how simulated data improves autonomy performance.

The position sits between sensor modeling, modern ML graphics, evaluation, and production autonomy, with references to NeRF, Gaussian splatting, generative models, and real sensor noise as relevant areas.

Qualifications

• Background in ML, robotics, computer science, or electrical engineering.
• Hands-on experience training and evaluating modern ML models.
• Strong Python skills and experience with deep learning frameworks.
• Experience with sensor modeling, 3D geometry, generative methods, or ML pipelines is a plus.

Responsibilities

• Research and implement synthetic sensor simulation methods
• Characterize the realism and utility of generated sensor data
• Answer evaluation questions about how sensor data affects autonomy performance
• Collaborate with autonomy, infrastructure, and systems teams on simulation needs

Skills

ML/robotics background

Python

Deep learning frameworks

3D geometry

Sensor modeling

Generative methods

ML model evaluation

Education

ML, robotics, CS, or EE background

Tools

PyTorch

TensorFlow

Job description

What the role actually is

Nuro is hiring a senior or staff ML engineer to build synthetic sensor simulation for autonomous driving. The listing focuses on methods that generate realistic camera, lidar, or radar data and then measure whether that simulated data improves autonomy performance.

The role sits between sensor modeling, modern ML graphics, evaluation, and production autonomy. Nuro explicitly mentions NeRF, Gaussian splatting, generative models, and real sensor noise as relevant areas.

What you would work on

• Research and implement synthetic sensor simulation methods
• Characterize the realism and utility of generated sensor data
• Answer evaluation questions about how sensor data affects autonomy performance
• Collaborate with autonomy, infrastructure, and systems teams on simulation needs

What they are asking for

• ML, robotics, computer science, or electrical engineering background
• Hands-on experience training and evaluating modern ML models
• Strong Python skills and experience with deep learning frameworks
• Experience with sensor modeling, 3D geometry, generative methods, or ML pipelines is a plus

Why this one is worth a look

Simulation quality is becoming a product constraint for autonomy teams. This role is interesting because it is not just building synthetic scenes; it is about whether simulated sensors actually help a robot learn, validate, and ship safer behavior.