Zoox
Senior Machine Learning Engineer - Perception 3D Segmentation
Employment
Full-timeFrom the employer
Full-time
Level
SeniorTeam
Autonomy Software / SoftwareCountry assessment
Not doable from Austria because the employer's own board marks it as not remote.
Our assessment is guidance. Confirm arrangements with the employer.
Skills mentioned in this posting
Job description
In this role, you will...
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Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow .
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Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities .
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Engineer temporal processing modules to improve the stability and consistency of predictions over time.
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Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints .
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Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering.
Qualifications
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MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience.
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Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures.
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Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration.
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Experience with multi-sensor fusion (Lidar, Camera, Radar) and handling temporal data sequences.
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Experience with occupancy networks, implicit representations (NeRF/Gaussian Splats), or scene flow estimation.
Bonus Qualifications
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Experience optimizing models for TensorRT/CUDA to achieve low-latency inference.
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Familiarity with sparse convolutions or query-based architectures for efficient 3D processing.
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Experience with Vision Language Model, or multi-modal 3D foundation model, or World Model, or VLA.