aimlroles

Senior Machine Learning Engineer - Perception 3D Segmentation

Zoox zoox.com Open · verified Oct 22, 2026
Hybrid Foster City Full-time Senior Machine Learning Engineering

At a glance

Senior Machine Learning Engineering role at Zoox. Foster City · full-time · $254,000–$350,000 base.

SalaryStated by Zoox
$254,000 – $350,000
Base salary for this role, in USD per year, as published in the posting.
RoleMachine Learning Engineering
SenioritySenior
LocationFoster City
WorkplaceHybrid
EmploymentFull-time
Base pay$254,000–$350,000
PostedJul 17, 2026 · 3mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build deep learning models that combine lidar, camera, and radar data to predict 3D occupancy, semantic labels, and scene flow
  • Create vision-led fusion methods that improve geometric understanding while relying less on sparse sensor inputs
  • Add temporal processing so predictions remain stable and consistent across sequences
  • Tune model designs for real-time vehicle inference under latency limits while extending high-fidelity range
  • Work with tracking, prediction, and planning teams to refine contours and free-space estimates for complex maneuvers

What you bring

  • An MS or PhD in computer science, robotics, machine learning, or a related area, plus at least six years in industry
  • Strong 3D computer vision and deep learning expertise, including voxel-based or bird's-eye-view model designs
  • Proficiency in Python and PyTorch for model development, along with some C++ experience integrating models
  • Hands-on work with lidar, camera, and radar fusion and temporally ordered sensor data

Who this fits

This senior role suits an experienced machine learning engineer focused on 3D perception and multi-sensor fusion. It is based in Foster City and listed as hybrid.

From the employer

The Perception team at Zoox is responsible for the robot’s understanding of the world, fusing data from Lidar, Radar, and Cameras to create a unified representation of the environment. In this role, you will contribute to the development of our next-generation 3D occupancy and segmentation networks. You will architect and optimize high-performance deep learning models that generate dense, temporally consistent voxel representations of the driving environment. This work is critical for enabling our vehicle to navigate complex urban scenarios, handle rare obstacles, and drive safely in tight spaces by providing precise geometry and motion estimates to downstream planners.

In this role, you will...

  • Design and implement state-of-the-art multi-modal sensor fusion architectures (Lidar, Camera, Radar) to predict 3D occupancy, semantic segmentation, and flow .

  • Develop "vision-first" fusion strategies to enhance geometric understanding and reduce dependency on sparse sensor modalities .

  • Engineer temporal processing modules to improve the stability and consistency of predictions over time.

  • Optimize model architectures for real-time on-vehicle inference, balancing high-fidelity range extension with strict latency constraints .

  • Collaborate with downstream consumers (Tracking, Prediction, Planner) to refine geometric outputs, such as contours and free-space estimations, for complex maneuvering.

Qualifications

  • MS or PhD in Computer Science, Robotics, Machine Learning, or related field with 6+ years of industry experience.

  • Deep expertise in 3D Computer Vision and Deep Learning, specifically with voxel-based or BEV (Bird's Eye View) architectures.

  • Strong proficiency in Python and deep learning frameworks (PyTorch) for model training and design as well as some experience in C++ for model integration.

  • Experience with multi-sensor fusion (Lidar, Camera, Radar) and handling temporal data sequences.

  • Experience with occupancy networks, implicit representations (NeRF/Gaussian Splats), or scene flow estimation.

Bonus Qualifications

  • Experience optimizing models for TensorRT/CUDA to achieve low-latency inference.

  • Familiarity with sparse convolutions or query-based architectures for efficient 3D processing.

  • Experience with Vision Language Model, or multi-modal 3D foundation model, or World Model, or VLA.

About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.