AI Hydrology Model Intern

Description

  

AEM (Advanced Environmental Monitoring) is the global leader in innovative mission critical weather, wildfire and water monitoring and intelligence solutions. We aim to be the world’s essential source for environmental insights – enabling decisive action and positive outcomes for our customers and their constituents. Our family of innovators offers world-class hydrometeorological technologies and services, including sensors, dataloggers, telemetry, and advanced analytics and software. Our technology and services empower the communities and organizations to survive – and thrive – in the face of escalating environmental risks.  

Job Responsibilities: 

You  will support an end-to-end comparison study of AI-assisted and AEM-conventional hydrologic model calibration. The project delivers benchmarking data, training materials, and a final recommendation report to help AEM hydrologists evaluate and adopt best practices.

• Assist in defining and documenting the AI vs. AEM model comparison framework.
• Support the Hydrology Team in running AEM model simulations and collecting AI model results.
• Help gather, organize, and validate historical hydrometeorological datasets for calibration testing.
• Participate in statistical performance analysis comparing auto-calibrated and manually calibrated models.
• Document and evaluate the auto-calibration feature in VFLO.
• Contribute to the development of training materials and best-practice documentation for AEM hydrologists.
• Assist the Project Lead in preparing the final report and recommendation by August 21, 2026.

This job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described, and may be amended at any time at the sole discretion of the Employer.

Requirements

 

• Currently enrolled in a degree program in Hydrology, Civil/Environmental Engineering, Water Resources, or a related field.
• Basic understanding of hydrologic modeling concepts and calibration principles.
• Familiarity with data analysis and statistical methods.
• Proficiency with standard data and document tools (Excel, Word, etc.).
• Strong written and verbal communication skills for documentation and reporting.
• Ability to work both independently and collaboratively within a multidisciplinary team.

Preferred Experience:

• Experience with hydrologic modeling software such as VFLO, HEC-HMS, or similar distributed models.
• Exposure to AI/ML concepts or data science methodologies in environmental applications.
• Experience handling hydrometeorological datasets.
• Coursework or project experience in model calibration and validation.

Additional Information:

• This is a remote opportunity that can be done from anywhere in the continental United States and/or Canada 
• Must be eligible to work in the U.S. or Canada without company sponsorship, now or in the future, for employment-based work authorization. F-1 visa holders with Optional Practical Training (OPT) who will require H-1B status, TNs, or current H-1B visa holders will not be considered. H1-B and green card sponsorship is not available for this position.

US Benefits include: Medical, Dental, Vision, Life Insurance, Short-Term & Long-Term Disability & 401k match of up to 3%. 

US Compensation Range: A reasonable estimate of the current salary range for this position is $19.00 - $26.00 USD / hour. Please note that the salary information is a general guideline only. AEM considers a wide range of factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education, licensure and certifications, key skills as well as other market and business considerations when extending an offer. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.

This position will accept applications on an ongoing basis and will be closed once the position is filled. 

AEM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.