Source Job

US Canada

  • Develop and train computer vision and deep learning models for road‑lane detection using monocular and multimodal sensor data.
  • Build 3D road surface and lane geometry models in BEV space and integrate them into Torc’s autonomy pipeline.
  • Analyze model performance, identify corner cases, and improve robustness under diverse environmental and long‑tail conditions.

Python PyTorch Machine Learning Computer Vision

4 jobs similar to ML Engineer, II - Road & Lane

Jobs ranked by similarity.

$153,200–$183,300/yr
US Canada

  • Develop and train deep learning models for camera-based perception.
  • Implement production-quality machine learning code to support model training, evaluation, and inference.
  • Analyze model performance across diverse driving scenarios to improve robustness and generalization.

Torc Robotics focuses on developing self-driving vehicle technology. They aim to make roads safer and improve lives by commercializing autonomous trucks, offering advanced driver assistance systems and self-driving solutions, with a focus on safety and reliability.

US Canada

  • Develop and train machine learning models for scene understanding.
  • Implement production-quality ML code to support model training.
  • Analyze model performance, identify failure modes, and propose improvements.

Torc Robotics is dedicated to developing autonomous driving technology. They aim to revolutionize the trucking industry with safe and efficient self-driving solutions.

US Canada

  • Develop and train machine learning models for learned behavior systems.
  • Implement production-quality ML code to support model training, evaluation, and inference.
  • Analyze model performance, identify failure modes, and propose improvements to increase robustness.

Torc Robotics develops behavior models that power decision-making for autonomous trucks. While the job posting does not provide specific information regarding company size, it can be inferred that they foster a highly collaborative environment.

Canada

  • Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets.
  • Identify and resolve bottlenecks in the training pipeline to maximize GPU utilization and reduce training time.
  • Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks.

Serve Robotics is reimagining how things move in cities. Their personable sidewalk robot is their vision for the future; it's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses. Their team is agile, diverse, and driven aiming to grow robotic deliveries from surprising novelty to efficient ubiquity.