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Machine Learning Nasa Jobs in Missouri (NOW HIRING)

These geospatial inputs and information will be used to fine-tune a NASA foundation model (Prithvi ... Strong programming skills and experience with machine learning applications in geoscience are ...

Machine Learning Nasa information

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$18.3K

$101.9K

$185.9K

How much do machine learning nasa jobs pay per year?

As of Aug 25, 2026, the average yearly pay for machine learning nasa in Missouri is $101,894.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,607.00 and $137,598.00 per year, depending on experience, location, and employer.

What does a machine learning specialist at NASA do?

Machine Learning specialists at NASA use advanced algorithms and data analysis techniques to help solve complex problems in space exploration and research. Their work includes developing models for spacecraft navigation, analyzing satellite imagery, predicting equipment failures, and supporting scientific discoveries through data-driven insights. By leveraging artificial intelligence and machine learning, they help NASA make more accurate predictions, automate processes, and enhance mission safety and efficiency.

What are the key skills and qualifications needed to thrive as a machine learning scientist at NASA?

To thrive as a Machine Learning Scientist at NASA, you need a solid background in computer science, mathematics, and statistics, typically supported by an advanced degree in a related field. Proficiency with programming languages like Python or R, familiarity with machine learning libraries (such as TensorFlow or PyTorch), and experience with large-scale data analysis are essential. Strong problem-solving skills, creativity, and the ability to collaborate across multidisciplinary teams help set top candidates apart. These skills and qualities are crucial for developing innovative AI solutions that support NASA’s scientific missions and research objectives.

What are common challenges faced by machine learning professionals working at NASA, and how can applicants prepare for them?

Machine learning professionals at NASA often work with complex, high-dimensional datasets collected from space missions, satellites, and simulations, which can present unique challenges such as data sparsity, noise, and the need for robust, interpretable models. Collaboration with scientists and engineers from diverse backgrounds is frequent, requiring excellent communication skills to translate technical findings into actionable insights. To prepare, applicants should familiarize themselves with domain-specific data, stay updated on the latest advancements in machine learning, and practice interdisciplinary teamwork to effectively contribute to NASA's innovative projects.

Does NASA use machine learning?

NASA employs machine learning techniques across various projects, including satellite data analysis, spacecraft navigation, and climate modeling. Machine learning helps improve data processing efficiency and supports autonomous systems in space exploration. Job roles in this field often require knowledge of data science, programming, and domain-specific applications.

What are popular job titles related to Machine Learning Nasa jobs in Missouri?

For Machine Learning Nasa jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Machine Learning Nasa jobs in Missouri look for?

The top searched job categories for Machine Learning Nasa jobs in Missouri are:

What cities in Missouri are hiring for Machine Learning Nasa jobs?

Cities in Missouri with the most Machine Learning Nasa job openings:

Postdoctoral Research Associate - Engineering

Washington University

Saint Louis, MO • On-site

Full-time

Posted 28 days ago


Job description

Location
ST. LOUIS, MO 63130Position Summary
The postdoc will be anticipated to leverage satellite retrievals of atmospheric composition, emissions and meteorology datasets, and a chemical transport model (CTM). These geospatial inputs and information will be used to fine-tune a NASA foundation model (Prithvi WxC) to emulate CTM processes, and to predict ground-level air quality data (e.g., PM2.5, NO2, and SO2) over the United Sates for electric utility air permitting. The postdoc will also have the opportunity to work on other topics related to air quality modeling, remote sensing, and machine learning within the scope of ACAG.
The postdoc will have various opportunities for professional development, including contributing to and leading grant proposal development (e.g., external postdoctoral fellowships) under the guidance of both mentors. Additional opportunities include delivering guest lectures to strengthen teaching experience, and receiving mentorship in preparing academia and industry job applications, and additional professional tutoring services from the Writing Center and Communication Center at WashU.
Job Description
Primary Duties & Responsibilities:
Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/.
Working Conditions:
This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals.
Salary Range:
Base pay is commensurate with experience.
The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.
Required Qualifications
Education:
Ph.D., M.D. Or Equivalent Terminal Or Doctoral Degree.
Certifications/Professional Licenses:
No specific certification/professional license is required for this position.
Work Experience:
No specific work experience is required for this position.
Skills:
Not Applicable
Driver's License:
A driver's license is not required for this position.
More About This Job
Preferred Qualifications:
  • PhD in a relevant subject, including but not limited to, atmospheric science, environmental engineering, earth observation, and computer science.
  • Strong programming skills and experience with machine learning applications in geoscience are highly desirable.
  • Experience of disseminating findings through publications and presentations.
  • Strong communication skills, with the ability to work both independently and collaboratively with a research team.

Preferred Qualifications
Education:
No additional education unless stated elsewhere in the job posting.
Certifications/Professional Licenses:
No additional certification/professional licenses unless stated elsewhere in the job posting.
Work Experience:
No additional work experience unless stated elsewhere in the job posting.
Skills:
Not Applicable
Questions
For frequently asked questions about the application process, please refer to our External Applicant FAQ.
Accommodation
If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request.
All qualified individuals must be able to perform the essential functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential functions of their job, absent undue hardship.
Pre-Employment Screening
All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening.
Benefits Statement
Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits.
EEO Statement
Washington University in St. Louis is committed to the principles and practices of equal employment opportunity. It is the University's policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, citizenship (where prohibited by federal law), age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information.