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Day 71
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Pay Range $102,000.00 to $108,000.00 depending on experience, education, and clearance level.Read the full posting
Employment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Design, develop and evaluate AI/ML methods for probabilistic hazard forecasts
Lead tools that integrate WoFS ensemble output with PHI systems
Merge WoFS forecasts with radar, satellite, lightning and environmental data
Lead user engagement and analysis through the Hazardous Weather Testbed
Run verification, visualization and explainability studies of forecast performance
Design, develop, and evaluate AI/ML methodologies that enhance the generation, interpretation, and communication of probabilistic hazard forecasts
Lead development and implementation of tools that integrate WoFS ensemble output with PHI systems and workflows
Develop methods to merge WoFS forecasts with meteorological observations (radar, satellite, lightning, environmental datasets)
Lead planning, facilitation, and analysis of user engagement activities conducted through the Hazardous Weather Testbed (HWT)
Conduct data analysis, visualization, verification, and explainability studies to evaluate forecast performance
8+ years of professional or academic experience (5 years of AI Experience preferred)
Experience conducting research involving severe convective storms, hazardous weather forecasting, or probabilistic prediction systems
Knowledge of ensemble forecasting systems, including Warn-on-Forecast (WoFS) or similar convection-allowing ensemble prediction systems
Experience applying artificial intelligence and/or machine learning techniques to meteorological, environmental, or geospatial datasets
Demonstrated experience leading a project team or providing limited supervision on a technical research effort
Proficiency in scientific programming and software development using Python and related data analysis and visualization tools
Required: - BS Degree (Advanced Degree Preferred) in meteorology, atmospheric science, computer science, data science, engineering, or a related field - 8+ years of professional or academic experience (5 years of AI Experience preferred)
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Day 71
Similar jobs usually come down between day 8 and day 76.
From 5,456 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Demonstrated experience leading a project team or providing limited supervision on a technical research effort - Proficiency in scientific programming and software development using Python and related data analysis and visualization tools - Experience working with large observational and model datasets, including radar, satellite, lightning, and environmental observations
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Rapidly updating, probabilistic severe weather guidance is only as good as the science and technology behind it. As FWI's PHI and AI/ML Research Specialist supporting NSSL, you will apply expert, highly specialized knowledge to advance Probabilistic Hazard Information (PHI) systems by integrating Warn-on-Forecast (WoFS) ensemble guidance, meteorological observations, and machine learning techniques into next-generation short-term hazard prediction tools. Your work will bridge research and operations — from designing AI/ML methodologies to leading Hazardous Weather Testbed (HWT) engagement with real NWS forecasters — to make severe weather guidance faster, smarter, and easier to act on, while providing technical guidance and limited supervision to project team members.
Work Schedule and Location:
Remote: This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST.
FWI is expanding rapidly and has been recognized as a 2024, 2025 and 2026 Top Workplace, offering excellent growth opportunities in a collaborative environment.
Required:
Desired:
Work Setting and Environment:
FWI is an Equal Opportunity Employer, including disability/vets.
At FWI, we place the highest importance on creating an exceptional employee experience. You'll have opportunities to achieve your career aspirations through internal promotions, professional development, and other recognition and rewards programs. Join our team and take advantage of the many benefits we offer, including:
$102,000.00 to $108,000.00 depending on experience, education, and clearance level.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Pay Range $102,000.00 to $108,000.00 depending on experience, education, and clearance level.
Location not supplied.
Work Schedule and Location: Remote: This full-time remote position will work Monday through Friday, 8 AM CST to 5 PM CST. FWI is expanding rapidly and has been recognized as a 2024, 2025 and 2026 Top Workplace, offering excellent growth opportunities in a collaborative environment.
Work Setting and Environment: - Primary location: Remote - Normal work hours are Monday through Friday, 8 hours per day / 40 hours per week, excluding federal holidays; field data-collection activities may require irregular hours during active severe weather events
No clear work-authorization passage found. Eligibility is unconfirmed.