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Geometric Deep Learning Jobs in Massachusetts (NOW HIRING)

Xometry

Staff Data Scientist

Waltham, MA · Hybrid

Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred given the focus on native 3D geometry * Strategic Delivery: Proven ability ...

Xometry

Staff Data Scientist

Waltham, MA · On-site

Deep expertise in Geometric Deep Learning, Computer Vision (3D mesh/B-Rep processing), or Generative AI is highly preferred given the focus on native 3D geometry * Strategic Delivery: Proven ability ...

Formlabs

AI Software Intern (Fall 2026)

Somerville, MA · On-site

As an AI Software Intern , you will apply machine learning and deep learning techniques to solve complex physical, geometric, and vision constraints in the additive manufacturing space. You will work ...

Cisco

Applied AI Scientist

Cambridge, MA · On-site

Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

Cisco

Applied AI Scientist

Waltham, MA

Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

Cisco

Applied AI Scientist

Boston, MA

Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

Cisco

Applied AI Scientist

Maynard, MA

Deep experience with graph representation learning, graph transformers (e.g., GCN/GAT/GraphSAGE ... Hands-on experience with frameworks such as PyTorch Geometric (PyG), DGL, GraphGym, GraphML systems ...

Varsity Tutors

Math 1 Tutor

Waltham, MA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

Varsity Tutors

Math 1 Tutor

Lawrence, MA · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of linear equations and inequalities, functions and function families, systems of ...

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All JobsGeometric Deep Learning JobsGeometric Deep Learning Jobs in Massachusetts

Geometric Deep Learning information

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.
What are popular job titles related to Geometric Deep Learning jobs in Massachusetts? For Geometric Deep Learning jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Geometric Deep Learning jobs in Massachusetts look for? The top searched job categories for Geometric Deep Learning jobs in Massachusetts are:
Geometric Deep Learning jobs near you
HMS - Postdoctoral Fellow in Zitnik Lab

HMS - Postdoctoral Fellow in Zitnik Lab

Harvard University

Cambridge, MA • On-site

$54K - $73K/yr

Full-time

Posted 27 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

81st of 611 rated colleges and universities

Job description

Position
Details
Title
HMS - Postdoctoral Fellow in Zitnik Lab
School
Harvard Medical School
Department/Area
Position Description
We invite applicants for a postdoctoral fellow position in the
Zitnik lab at Harvard Medical School in Boston
Massachusetts. The work of the Zitnik lab is focused on
Artificial Intelligence for Medicine and Science.
The selected candidates will lead research in generative,
multimodal, and agentic AI, as well as foundation models,
with a focus on geometric deep learning, large-scale
knowledge graphs, and large language models. Fellows will
also have the opportunity to apply these methods to address
challenges in scientific discovery and precision medicine.
We seek highly-motivated applicants with background in one
or more of the following areas: agentic AI, geometric deep
learning, large-scale knowledge graphs, large language
models, multimodal learning, and generative AI. Successful
applicants will be strong technically as well as have an
inclination towards real-world problems. Ideal candidates will
have demonstrably strong research skills, evidenced by
multiple publications in top-tier machine learning or artificial
intelligence conferences and/or leading scientific journals.
Salary and Benefits
This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines.
With this appointment, you are represented by the Harvard Academic Workers (HAW) - UAW for purposes of collective bargaining and matters affecting your compensation and working conditions.
Basic Qualifications
  • Ph.D. or M.D./Ph.D. in areas such as machine
    learning, computer science or closely related field.
    Excellent programming skills and practical
    experience with leading machine learning
    frameworks and modern AI environments, including
    multi-GPU model training and large-scale inference
    on dozens to hundreds GPUs, are required.

Additional Qualifications
Experience in applications of AI to biology and
medicine is a strong plus.
Special Instructions
Required documents:
CV
Research summary of PhD work.
Cover letter describing your interest in the lab and
initial ideas for new research directions or projects you
could undertake in the lab.
A NOTE with the names and contact information for
three people who have agreed to serve as a reference.
Please submit application documents through the ARIeS portal.
Expected Dates:
Duration: This is a one-year term position from the
date of hire, with the possibility of extension,
contingent upon work performance, business need,
and continued funding to support the position.
With this appointment, you are represented by the Harvard
Academic Workers (HAW) - UAW for purposes of collective
bargaining and matters affecting your compensation and
working conditions.
Harvard has an equal employment opportunity policy that
outlines our commitment to prohibiting discrimination on the
basis of race, sex, ethnicity, color, national origin, religion,
disability, or any other characteristic protected by law or
identified in the university's non-discrimination policy.
Contact Information
Heather Viana
10 Shattuck St.
Boston, MA 02115
Contact Email
heather_viana@hms.harvard.edu
Salary Range
Information regarding postdoctoral fellow salary, which is determined by the number of years post-PhD, can be found at https://postdoc.hms.harvard.edu/guidelines.
Minimum Number of References Required
Maximum Number of References Allowed
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