ML Engineer, II - Camera Models

Meet the Team: 
As a Machine Learning Engineer II – Camera Models, you will help develop and deploy machine learning models that power camera-based perception for autonomous trucks. The Camera Models team builds and maintains core vision models that enable the autonomy stack to understand the environment, detect and localize objects, and estimate scene structure from camera data. 

 

Working closely with teams across perception, data, and infrastructure, you will contribute to building robust and scalable camera-based models that support safe and reliable autonomous driving in real-world freight operations. 
 
This role focuses on developing high-performance vision models and the infrastructure needed to train, evaluate, and deploy them at scale. 
 
What You’ll Do 

• Develop and train deep learning models for camera-based perception, enabling the autonomy stack to detect objects, understand scenes, and estimate geometric information from visual inputs. 

• Implement production-quality machine learning code to support model training, evaluation, and inference for camera perception systems. 

• Analyze model performance across diverse driving scenarios, identify failure modes, and improve robustness and generalization. 

• Contribute to the development and optimization of large-scale training pipelines, including dataset preparation, distributed training, and experiment management. 

• Work closely with data teams to curate and improve training datasets derived from fleet logs, simulation, and annotation pipelines. 

• Collaborate with cross-functional teams across perception, simulation, and validation to evaluate model performance and support integration into the autonomy stack. 

• Improve experimentation workflows and tooling to accelerate model iteration, reproducibility, and evaluation. 

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