Hydrologic Modeler - ML-Driven Watershed Forecasting

Visa Hunt; United States; On-site; USD 110,000 - 165,000; Full time

Benefits offered by this job

Healthcare

PTO

401(k) matching

Employee Stock Ownership Plan (ESOP)

Learning & development

Flexible spending accounts

Job summary

Lynker Corporation seeks a Hydrologic Modeler to join its Modeling team in the United States. The role focuses on training, evaluating, and deploying physics-based and machine-learning hydrologic models across regional to continental domains using Python and PyTorch.

You will generate model forcings, manage training data, and collaborate across Modeling, Science, and Platform teams to produce reproducible results and publishables, including open-source contributions.

Qualifications

• The candidate has a master's degree or equivalent experience in hydrology or related fields.
• Experience with hydrologic modeling, both physics-based and machine-learning approaches.
• Strong programming skills in Python and deep-learning frameworks.

Responsibilities

• Train, execute, and synthesize large-scale hydrologic models across regional to continental domains.
• Analyze results, calibrate and validate models, quantify uncertainty, and communicate findings.
• Generate and quality-check model forcings and manage training data.

Skills

Python

Git

Linux

Time-series data handling

Large-scale modeling

Education

Master's in hydrology, water resources, engineering, hydrologic sciences, applied mathematics, computer science, or related field

Bachelor's degree + 2 years training and running hydrologic, physics-based, and/or machine-learning models

Tools

NeuralHydrology

dHBV

Next Generation Water Resource Modeling Framework

Job description

Lynker Corporation seeks a Hydrologic Modeler to join its Modeling team in the United States. The role focuses on training, evaluating, and deploying physics-based and machine-learning hydrologic models across regional to continental domains using Python and PyTorch.

You will generate model forcings, manage training data, and collaborate across Modeling, Science, and Platform teams to produce reproducible results and publishables, including open-source contributions.