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Graph Machine Learning Postdoc Jobs (NOW HIRING)

Machine Learning Engineer As a Machine Learning Engineer , you will play a critical role in ... Exposure to graph databases (e.g., Neo4j). * Familiarity with CI/CD tools (e.g., Jenkins). * Domain ...

Machine Learning Engineer - Generative Al Long term contract Sunrise, FL (Hybrid-3 days onsite ... Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google ...

As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI ... EKS, Graph database), API and in-memory technologies * Strong knowledge of developing highly ...

Sr Machine Learning Engineer

San Jose, CA ยท On-site

$143K - $189K/yr

Experience implementing and enhancing graph-based and relational machine learning techniques for structured or graph data (1 year) 14. Experience performing data preprocessing, feature engineering ...

Required: * 6+ years of work experience building and deploying machine learning systems into ... Experience with graph data and graph-based models (e.g., PyTorch Geometric) * Experience with model ...

Sr Machine Learning Engineer

San Jose, CA

$143K - $189K/yr

Experience implementing and enhancing graph-based and relational machine learning techniques for structured or graph data (1 year) 14. Experience performing data preprocessing, feature engineering ...

Sr Machine Learning Engineer

San Jose, CA

$143K - $189K/yr

Experience implementing and enhancing graph-based and relational machine learning techniques for structured or graph data (1 year) 14. Experience performing data preprocessing, feature engineering ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI ... EKS, Graph database), API and in-memory technologies * Strong knowledge of developing highly ...

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Graph Machine Learning Postdoc information

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How much do graph machine learning postdoc jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for graph machine learning postdoc 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 are some common interdisciplinary collaborations for a Graph Machine Learning Postdoc?

As a Graph Machine Learning Postdoc, you will frequently collaborate with researchers and practitioners from diverse domains such as biology, social sciences, and computer vision. These collaborations often involve integrating graph-based models with domain-specific data, which can introduce unique challenges like aligning data formats and objectives. Working closely with domain experts enhances your research impact and can lead to co-authored publications, opening doors for future academic or industry roles. Regular interdisciplinary meetings and joint projects are common, fostering a dynamic and supportive work environment.

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

AspectGraph Machine Learning PostdocData Scientist
Required CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; some roles prefer PhD
Work EnvironmentAcademic research labs, universities, research institutionsCorporate, tech companies, startups, or consulting firms
Industry UsagePrimarily academia and research projectsBusiness analytics, product development, decision-making
Common Search & ComparisonYesYes

The Graph Machine Learning Postdoc typically focuses on academic research, exploring advanced algorithms and theories in graph-based learning, often within universities or research institutions. In contrast, Data Scientists apply data analysis and machine learning techniques to solve practical business problems in industry settings. While both roles require strong technical skills, the Postdoc emphasizes research and publication, whereas Data Scientists focus on deploying models for business insights.

What is a Graph Machine Learning Postdoc?

A Graph Machine Learning Postdoc is a researcher who has recently completed their PhD and is conducting advanced studies focused on machine learning techniques for graph-structured data. This role typically involves developing new algorithms, analyzing complex networks, and publishing findings in academic journals. Graph machine learning is used in applications such as social network analysis, drug discovery, and recommendation systems. Postdocs often collaborate with other researchers and may mentor graduate students while working towards establishing their own research profile.

What are the key skills and qualifications needed to thrive as a Graph Machine Learning Postdoc, and why are they important?

To thrive as a Graph Machine Learning Postdoc, you need a strong background in mathematics, machine learning, and graph theory, often demonstrated by a PhD in computer science, mathematics, or a related field. Proficiency with programming languages such as Python, frameworks like PyTorch or TensorFlow, and graph libraries (e.g., DGL, PyTorch Geometric) is essential. Excellent problem-solving skills, communication abilities, and a collaborative mindset help you excel in research environments and interdisciplinary projects. These skills and qualities are crucial for developing innovative graph-based models, advancing scientific knowledge, and effectively sharing findings with the academic community.
Infographic showing various Graph Machine Learning Postdoc job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 4% Temporary, and 8% Contract. Highlights an 77% In-person, and 23% Remote job distribution, with an average salary of $54,803 per year, or $26.3 per hour.
ML Postdoc Researcher - LLMs & Generative AI

ML Postdoc Researcher - LLMs & Generative AI

Truveta

Seattle, WA โ€ข Remote

$132K/yr

Other

Posted 4 days ago


Job description

ML Postdoc Researcher - LLMs & Generative AI

Truveta is the world's first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta' s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture. ย Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote

Who We Needย 

We are seeking a highly motivated and talented Machine Learning Postdoctoral Researcher to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

Program Details

Our Postdoctoral Research program is designed for candidates who have completed their PhD within the last two years and worked in their area of expertise since graduation as a postdoc, professor, or industry researcher/scientist. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our postdoc research programs are designed to be a minimum of 3 months and a maximum of 12 months, with the opportunity to extend beyond the initially agreed term based on the company's needs and the candidate's desires.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In this role, you will:

  • Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
  • Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
  • Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
  • Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
  • Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

  • Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
  • Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
  • Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
  • Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
  • Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
  • Strong communication skills and the ability to work effectively in a collaborative research environment

Preferred Qualifications

  • Experience with distributed parallel training, large-scale multi-modal foundation and generative models
  • Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
  • Familiarity with training multi-modal foundation models
  • Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
  • A track record of publications and contributions to the machine learning and natural language processing communities

This postdoctoral research program offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare domain. Join us and make a significant impact on the future of healthcare and patient well-being.

Why Truveta?ย 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together.ย 

We offer:ย 

  • Competitive compensation
  • Company-issued laptop and equipment
  • Opportunities for future full-time positions
  • The range for this position is $50-$60 per hour

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don't meet all of the requirements.