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Geometric Deep Learning Jobs in California (NOW HIRING)

PlusAI

Computer Vision Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

Ensure alignment and geometric consistency between different sensor modalities within the ... Deep understanding of machine learning principles and methodologies * Experience with implementing ...

Amazon

Senior Applied Scientist

San Francisco, CA · On-site

$107K - $147K/yr

You will develop ML-based methods to extract semantic and geometric information from radar point ... You will lead research that translates cutting-edge advances in deep learning and computer vision ...

The Bot Company

3D Vision

San Francisco, CA · On-site

$200K - $350K/yr

Develop geometric vision pipelines-SLAM, reconstruction, tracking-and integrate them with learned models. * Implement and optimize deep learning models for depth, flow, correspondence, and 3D ...

The Bot Company

3D Vision

San Francisco, CA · On-site

Develop geometric vision pipelines-SLAM, reconstruction, tracking-and integrate them with learned models. * Implement and optimize deep learning models for depth, flow, correspondence, and 3D ...

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All JobsGeometric Deep Learning JobsGeometric Deep Learning Jobs in California

Geometric Deep Learning information

What is the difference between Geometric Deep Learning vs Data Scientist?

AspectGeometric Deep LearningData Scientist
Required CredentialsAdvanced degrees in computer science, machine learning, or related fieldsBachelor's or master's in data science, statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness analytics, product teams, consulting firms
Industry UsageAI, robotics, computer vision, graph analysisBusiness intelligence, marketing, finance, healthcare

Geometric Deep Learning focuses on applying deep learning techniques to non-Euclidean data like graphs and manifolds, often requiring advanced technical skills. Data Scientists analyze and interpret data to inform business decisions, typically working with structured data and statistical tools. While both roles involve data analysis, Geometric Deep Learning is more research-oriented and specialized in AI development, whereas Data Scientists focus on practical data insights across industries.

What are some common challenges faced when working on geometric deep learning projects, and how can they be addressed?

One common challenge in Geometric Deep Learning is dealing with the complexity and diversity of data structures, such as graphs, point clouds, or manifolds. These data types often require specialized neural network architectures and custom preprocessing steps, which can be more complex than traditional deep learning tasks. Collaboration with domain experts and staying updated with the latest research are crucial for overcoming these obstacles. Additionally, debugging and visualizing the learning process can be more challenging, so employing robust evaluation metrics and visualization tools is highly recommended.

What are the key skills and qualifications needed to thrive as a geometric deep learning engineer?

To excel as a Geometric Deep Learning Engineer, you need a strong background in mathematics, machine learning, and computer science, typically supported by an advanced degree in a related field. Proficiency with deep learning frameworks like PyTorch or TensorFlow, as well as experience with graph neural networks (GNNs) and geometric data structures, is essential. Strong analytical thinking, problem-solving abilities, and collaborative communication are key soft skills for innovating and working with interdisciplinary teams. These skills are crucial for developing cutting-edge models that leverage geometric data, enabling impactful solutions across domains such as computer vision, biology, and social network analysis.

What are popular job titles related to Geometric Deep Learning jobs in California?

For Geometric Deep Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Geometric Deep Learning jobs in California look for?

The top searched job categories for Geometric Deep Learning jobs in California are:

What cities in California are hiring for Geometric Deep Learning jobs?

Cities in California with the most Geometric Deep Learning job openings:

Geometric Deep Learning jobs near you
Infographic showing various Geometric Deep Learning job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 87% In-person, and 13% Remote job distribution.

Senior Machine Learning Engineer - Perception 3D Segmentation

Zoox

Foster City, CA • On-site

$242K - $290K/yr

Full-time

Medical, Life, PTO

Re-posted 13 hours ago

Job description

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.

$242,000 - $290,000 a year
Base Salary Range
 
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox 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.

Follow us on LinkedIn

Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] 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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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