1

Graph Machine Learning Jobs (NOW HIRING)

... machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train ... Collaborate on connecting upstream Graph Neural Networks (GNNs) or LLMs mapping schematic ...

... graph compiler/scheduling). • Performs platform research to enable new machine learning compute paradigm (e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated ...

... graph compiler/scheduling). • Performs platform research to enable new machine learning compute paradigm (e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated ...

... graph compiler/scheduling). * Performs platform research to enable new machine learning compute paradigm (e.g., compute in memory, on‑device learning/training, edge‑cloud distributed/federated ...

Optimize knowledge graph algorithms for performance, scalability, and reliability. * Conduct research on cutting-edge Machine Learning, NLP, and knowledge graph techniques, evaluating external data ...

Familiarity with graph algorithms, graph machine learning (GNNs), or leveraging Knowledge Graphs to enhance Large Language Model architectures via Graph RAG (Retrieval-Aug Generation). Benefits ...

Senior Machine Learning Systems Engineer

$107K - $146K/yr

The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure ... Zero-to-one development and support of a graph ML codebase and platform that abstracts away common ...

The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure ... Zero-to-one development and support of a graph ML codebase and platform that abstracts away common ...

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D ... graph neural networks, geodesic computations, or neural implicit representations (e.g., NeRF ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g ...

Showing results 41-60

Graph Machine Learning information

See salary details

$13

$26

$48

How much do graph machine learning jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for graph machine learning in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $27.88 per hour, depending on experience, location, and employer.

What is the difference between Graph Machine Learning vs Data Scientist?

AspectGraph Machine LearningData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of graph theory and machine learningDegree in Statistics, Computer Science, or related fields; proficiency in data analysis and programming
Work EnvironmentResearch labs, tech companies, AI startups focusing on graph dataBusiness, finance, healthcare, and tech industries analyzing diverse data sets
Industry UsageSpecialized in graph data analysis and machine learning models on graph structuresBroad data analysis, modeling, and insights across various sectors

Graph Machine Learning focuses on developing algorithms for graph-structured data, while Data Scientists analyze and interpret diverse data sets across industries. Both roles require strong analytical skills, but their focus areas and tools differ significantly.

What cities are hiring for Graph Machine Learning jobs?

Cities with the most Graph Machine Learning job openings:

Infographic showing various Graph Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $54,803 per year, or $26.3 per hour.

Software Machine Learning Engineer (Teradyne, North Reading, MA)

North Reading, MA • On-site

Teradyne
Manufacturing • 1 - 5K employees

$116K - $186K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted just now


Job description

We are the global test and automation specialists, powering next-generation technologies through sophisticated solutions. Behind every electronic device you use, Teradyne's test technology ensures your device works right the first time, every time! Our portfolio of automation solutions help manufacturers to develop and deliver products quickly, efficiently and cost-effectively. Together, Teradyne companies deliver manufacturing automation across industries and applications around the world!

We attract, develop, and retain a high-performance workforce, comprised of people with diverse backgrounds and a shared drive for excellence. We strive to foster a positive and inclusive work environment that helps employees, and communities, thrive.

Our Purpose

TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are supported to innovate and learn something new every day.


We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team - one that makes better decisions, drives innovation and delivers better business results.


Opportunity Overview

As a Machine Learning Engineer, you will design, develop, and deploy applied AI solutions with a good knowledge on graph machine learning, reinforcement learning, and interpretable AI.

You will work closely with cross-functional teams to build scalable ML systems that model complex relationships in engineering data, optimize decision-making processes, and provide transparent, explainable insights. This role emphasizes hands-on development, experimentation, and collaboration rather than technical leadership.

  • Design and implement pipelines for training, evaluation, and deployment of ML models.
  • Apply graph ML methods to model relationships in structured and unstructured data.
  • Build and experiment with reinforcement learning algorithms (e.g., policy gradients, PPO, Q-learning) for optimization and decision-making tasks.
  • Incorporate interpretability and explainability techniques (e.g., SHAP, LIME, attention-based methods) into ML systems.
  • Collaborate with software, product, and application engineering teams to integrate ML solutions into production systems.
  • Assist in defining evaluation metrics and validation strategies for ML models.
  • Work with internal stakeholders to understand engineering workflows and translate them into ML-driven solutions.
  • Contribute to improving ML infrastructure, tooling, and best practices.
  • Experience with AI orchestration or agent frameworks (e.g., LangChain, AutoGen, etc.) is a plus.


All About You

We seek individuals who share our passion and determination. Our commitment to customer success drives us to go the extra mile. If you're ready to join us in this mission, take a closer look at the minimum criteria for the position.

  • 2+ years of experience in machine learning, applied AI, or related fields.
  • Hands-on experience building and deploying ML models.
  • Exposure to production ML systems (MLOps, monitoring, deployment) is desirable.
  • Ability to work collaboratively across teams.Strong analytical and problem-solving skills.
  • Basic understanding of software engineering practices and version control.
  • Ability to work cross-functionally with product, software, and hardware teams.
  • Strong communication skills; comfortable engaging directly with customers and stakeholders.
  • Strong problem-solving and reasoning skills
  • Master's or Ph.D. in Computer Science, Electrical Engineering, or related field (or equivalent industry experience).

 We are only considering candidates local to position location and are unable to provide relocation for this position.

 

Compensation:

The base salary range for this role is $116,500-$186,400. This range is a good faith estimate, and the amount of base salary will correspond with experience and skill set. This range can also fluctuate depending on demand and location.


Incentive Plan: This job is eligible for discretionary bonus(es) based on financial performance.

Benefits:

Teradyne offers a variety of robust health and well-being benefit programs, including medical, dental, vision, Flexible Spending Accounts, retirement savings plans, life and disability insurance, paid vacation & holidays, tuition assistance programs, and more.  Please click here to see details.