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Postdoctoral Machine Learning Jobs in Seattle, WA

Meta

Fundamental AI Researcher - FAIR

Seattle, WA · On-site

$154K/yr

Experience holding an industry, postdoctoral, faculty, or government researcher position * Research background in machine learning, artificial intelligence, computational statistics, applied ...

Fred Hutch

Post-Doctoral Research Fellow

Seattle, WA · On-site

$55.80K - $75.70K/yr

Responsibilities Specifically, the postdoc will have the following duties: * Developing new ... Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to ...

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How much do postdoctoral machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for postdoctoral machine learning in Seattle, WA is $67,168.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,800.00 and $75,700.00 per year, depending on experience, location, and employer.

What is a Postdoctoral Machine Learning job?

A Postdoctoral Machine Learning job is a research-focused position for individuals who have recently earned a Ph.D. in machine learning, artificial intelligence, or a related field. It typically involves conducting advanced research, publishing papers, collaborating with academic or industry partners, and developing novel algorithms or models. These roles are often hosted by universities, research institutes, or tech companies. The position helps researchers gain additional expertise and contribute to cutting-edge advancements before transitioning to faculty, industry, or independent research roles.

What are the key skills and qualifications needed to thrive in the Postdoctoral Machine Learning position, and why are they important?

To thrive as a Postdoctoral Machine Learning researcher, you need a strong background in machine learning theory, statistical analysis, and programming, typically supported by a Ph.D. in computer science, engineering, or a related quantitative field. Experience with Python, TensorFlow, PyTorch, and advanced data analytics tools is highly valued, as are relevant publications and experience with version control systems like Git. Strong problem-solving abilities, clear communication skills, and effective teamwork are crucial to excel in collaborative research settings. These skills and qualities are essential to drive innovative research, efficiently navigate complex datasets, and contribute to impactful scientific discoveries.

What are the typical daily responsibilities of a Postdoctoral Machine Learning researcher?

A Postdoctoral Machine Learning researcher typically spends their day designing and implementing machine learning algorithms, analyzing experimental results, and preparing manuscripts for publication. They often collaborate with interdisciplinary teams of scientists and engineers, attend lab meetings, and contribute to grant writing or project proposals. Regular activities also include keeping up with recent scientific literature, mentoring graduate or undergraduate students, and presenting research findings at conferences or seminars. The blend of technical development and scientific communication makes each day dynamic and offers opportunities to influence both academia and industry.
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Postdoctoral Machine Learning jobs near you
Postdoctoral Scholar - Machine Learning for Extreme Weather Events

Postdoctoral Scholar - Machine Learning for Extreme Weather Events

University of Washington

Seattle, WA • On-site

$6.68K - $6.76K/mo

Full-time

Posted 23 days ago

University Of Washington School Of Medicine rating

7.8

Company rating: 7.8 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

171st of 528 rated colleges and universities

Job description

Description
Professor Greg Hakim in the Department of Atmospheric and Climate Science at the University of Washington is seeking a full-time (100% FTE) postdoctoral scholar to investigate extreme events in historical climate. Building on reconstructions of the climate of the last millennium, we seek to understand the range of variability of extreme heatwaves, coldwaves, tropical cyclones and other weather events. This research involves the use of machine-learning weather models for sampling these extreme events conditioned on the climate state. This position is part of a larger team spread across three universities with the common goal of understanding weather events constrained by historical climate variability.
This position is full-time (100% FTE) with an initial term appointment of one year (12 months), renewable depending on funding and/or satisfactory performance for a total period of up to 2 years. The salary for this position will be $6,681-$6,761 per month, commensurate with experience and qualifications, or as mandated by a U.S. Department of Labor prevailing wage determination. The position is available starting March 6, 2026. The review process will commence immediately upon receipt of applications and will continue until filled. The anticipated start date is June 1, 2026. Priority consideration will be given to applications received by April 1, 2026.
Postdoctoral scholars at UW are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria apply. For more information, please visit the University of Washington Labor Relations website.
Postdoctoral scholars are engaged in full-time, mentored advanced training to enhance professional skills and research independence. Given the close mentoring relationship necessitated by the nature of postdoctoral scholar appointments; access to the full university community to support individual development; and, if applicable, visa sponsorship requirements, postdoctoral scholars must be physically present at their place of work on University property to fulfill their appointment duties.
University of Washington postdoctoral scholar appointments are for a temporary, defined period not to exceed five years/60 months, including any previous postdoctoral experience.
Qualifications
Minumum Qualifications
  • Candidates must have completed a PhD or foreign equivalent in Atmospheric Science or a related discipline.
  • Experience running weather and/or climate models.

Desired Qualifications
  • Experience with machine learning methods, including emulators of weather and climate dynamics.
  • Experience with modern computing environments, including Python, Linux, and agentic workflows
  • Strong analytical and writing skills as demonstrated by a record of publication in peer-reviewed journals.
  • Experience working effectively independently and in a collaborative group.

Application Instructions
To apply, candidates will submit materials via Interfolio, comprising
  • A letter of interest describing their skills, experience, and research interests
  • A curriculum vitae, including a list of publications and links to any open code repositories
  • Two representative publications
  • The names and contact information for three references. PDF files are preferred.

Equal Employment Opportunity Statement
Equal Opportunity
The University of Washington is committed to fostering an inclusive, respectful and welcoming community for all. As an equal opportunity employer, the University considers applicants for employment without regard to race, color, creed, religion, national origin, citizenship, sex, pregnancy, age, marital status, sexual orientation, gender identity or expression, genetic information, disability, or veteran status consistent with UW Executive Order No. 81.
Benefits Information
The University is committed to providing excellent benefits to our faculty. For a summary of available benefits, please see UWHR benefits information.
Privacy Notice
Your application materials may be used for employment consideration and shared in accordance with UW's Privacy Policy.
Disability Services
The University of Washington is committed to providing access and reasonable accommodation in its services, programs, activities, education, and employment for individuals with disabilities. To request disability accommodation in the application process, contact the Disability Services Office at 206-543-6450 or dso@uw.edu.

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