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Geometric Deep Learning Jobs (NOW HIRING)

Mach9 Robotics Inc

Head of ML

San Francisco, CA · On-site

Background in machine learning for 3D perception - point cloud understanding, 3D detection/segmentation, geometric deep learning, or related areas. * Experience with CAD AI, design automation, or ...

ZeroRFI

Lead ML Engineer

San Francisco, CA · Remote

$104K - $138K/yr

Implement graph neural networks and geometric deep learning models for BIM/IFC data analysis, spatial coordination, and MEP system optimization. * Integrate ML models with industry-standard tools ...

New

Astera

General DiffUSE Job Application

Emeryville, CA · On-site

$100K - $300K/yr

ML on raw experimental data rather than processed structures * 3D vision and geometric deep learning backgrounds especially welcome Dataset generation and open release * Designing and running ...

Xometry

Senior Director & Product Lead

Waltham, MA · Hybrid

$251K - $263K/yr

You can go toe-to-toe with Staff Engineers and Data Scientists on topics like geometric deep learning, native 3D geometry processing, and cloud-to-enterprise security architectures. * "Super IC ...

Xometry

Senior Director & Product Lead

North Bethesda, MD · Hybrid

$233K - $244K/yr

You can go toe-to-toe with Staff Engineers and Data Scientists on topics like geometric deep learning, native 3D geometry processing, and cloud-to-enterprise security architectures. * "Super IC ...

State Affairs

Software Engineer, Applied AI

Washington, DC · On-site

$165K - $250K/yr

... geometric deep learning, large language models (LLM), and generative AI * Ability to operate a Vector Database * Ability to program in TypeScript and Python * Ability to pre-train and fine tune large ...

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All JobsGeometric Deep Learning Jobs

Geometric Deep Learning information

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$11K

$83.9K

$140K

How much do geometric deep learning jobs pay per year?

As of Jul 5, 2026, the average yearly pay for geometric deep learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is geometric deep learning?

Geometric deep learning is a branch of machine learning focused on designing neural networks that operate on non-Euclidean data such as graphs and manifolds. It involves techniques like graph neural networks and requires understanding of both deep learning and geometric structures, often using tools like PyTorch or TensorFlow. Professionals in this field develop models for applications like social network analysis, 3D shape recognition, and molecular modeling.

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, and why are they important?

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.

Which 5 jobs will survive AI?

Geometric Deep Learning specialists are likely to continue in demand due to their expertise in advanced neural network architectures and 3D data processing. Jobs involving complex problem-solving, creativity, and domain-specific knowledge—such as data scientists, AI researchers, software engineers, cybersecurity analysts, and healthcare professionals—are expected to persist as AI tools augment rather than replace these roles. Continuous learning and proficiency with AI frameworks like TensorFlow or PyTorch enhance job security in these fields.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries like technology or finance. These roles often require expertise in programming, system design, and sometimes leadership or management responsibilities.
More about Geometric Deep Learning jobs
What cities are hiring for Geometric Deep Learning jobs? Cities with the most Geometric Deep Learning job openings:
What states have the most Geometric Deep Learning jobs? States with the most job openings for Geometric Deep Learning jobs include:
What job categories do people searching Geometric Deep Learning jobs look for? The top searched job categories for Geometric Deep Learning jobs are:
Geometric Deep Learning jobs near you
Infographic showing various Geometric Deep Learning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

AI Research Scientist/Manager - Spatial Reasoning

P-1 AI

San Francisco, CA • On-site

$200K - $385K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Job description

TL;DR: If you:
  • think deeply about how machines reason about the physical world;
  • have a track record of exceptional research or engineering achievement;
  • move effortlessly between papers, experiments, and production code;
  • love difficult problems with no obvious solution...

... you should apply for this role!
About P-1 AI:
At P-1 AI, we are building an AI engineer agent for the physical world named Archie. We maximize Archie's anthropomorphism so that he fits seamlessly into existing engineering teams and workflows in the form factor of a human engineer. Archie today is at the level of a junior mechanical and electrical engineer, with a quantitative intuition over the product design space and the ability to use complex engineering tools-the same tools his human teammates use. Archie's tech stack includes a custom agentic harness, structured design representation, continual skills learning, and small custom post-trained models (SFT and RLVR) using proprietary semi-synthetic training data sets and environments which create a deep competitive moat. Our ultimate aim is to build engineering ASI. We are backed in our mission by some of the top venture investors and AI luminaries.
About the opportunity:
We're seeking an exceptional AI Research Scientist/Manager to join our small team of elite researchers and help us push the boundaries of AI applied to the physical world. This role blends cutting-edge AI research with hands-on engineering, and is ideal for someone who thrives at the intersection of ideas and implementation.
About the role:
  • Research and develop new approaches for spatial reasoning, geometric understanding, physical reasoning, and structured world modeling in large-scale AI systems.
  • Own the full development pipeline from data generation to evaluation to product integration.
  • Contribute to both research strategy and technical implementation-this is a hands-on role. Have ownership over your own applied research stream.
  • Investigate topics such as 3D reasoning, geometric representations, multimodal reasoning, world models, simulation, and physical intuition.
  • Stay on the edge of what's possible and bring promising ideas into reality (e.g. following the literature, attending conferences, etc).

About you:
  • Have conducted research in one or more areas such as spatial reasoning, geometric deep learning, 3D vision, multimodal reasoning, world models, robotics, simulation, or related fields.
  • Are fluent in Python and modern ML stack such as PyTorch or JAX, and distributed training frameworks.
  • Creative approach to bringing definition and solutions to under-specificed challenges.
  • Are fascinated by how intelligent systems perceive, represent, and reason about the physical world.
  • Thrive in fast-moving, collaborative environments, and communicate technical matters with clarity.
  • Take a high-ownership, "make it work" approach to problem solving.

As a bonus, you may have:
  • A PhD (or equivalent experience) in Computer Science, Robotics, Engineering, Math, or a related field.
  • Publications in top-tier venues.
  • Experience working with CAD data, point clouds, meshes, simulation environments, or other geometric representations.

Location:
Onsite in San Mateo, CA. Relocation support available.
Benefits:
Competitive salary, meaningful equity ownership, healthcare, dental, vision, 401(k) match, and unlimited PTO.
Interview process:
  • Initial screening call (30 mins)
  • Biographical/behavioural interview (60 mins)
  • Technical interview (75 mins)
  • CEO interview (30 mins)

Apply