Lynker
Hydrologic Modeler
Boulder, CO, US
Sponsorship not specified$80k-$120kDetected 21 hours ago
PythonGitMachine LearningScientific WritingCollaboration
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odds of building a lasting career here
47Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level II)66
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~30% per draw at Level II). Good if you win; have a cap-exempt backup on your list.
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About the role
- Overview Lynker Corporation is a leading provider of innovative solutions in weather and climate science.
- Synthesis & interpretation: analyze model results to characterize performance, flow signatures, and hydrologic behavior, and communicate findings to the modeling team.
Responsibilities
- With a commitment to excellence and a passion for innovation, Lynker leverages cutting-edge technologies and scientific expertise to support the creation and delivery of improved operational weather forecasts.
- calibrate, benchmark, and validate models, quantify uncertainty, and diagnose where and why predictions succeed or fail.
- generate and quality-check model forcings and manage the training processes and datasets that drive these models.
- help develop, test, and improve hydrologic and hydraulic routing tools, primarily in Python.
- Experience developing or applying hydrologic and hydraulic routing methods.
Requirements
- Experience with high-performance or parallel computing for large-scale model runs.
Skills
- ML/AI methods: apply deep-learning approaches to hydrologic prediction, including tools such as NeuralHydrology and dHBV.
Compensation
- Lynker's benefits include the following: Comprehensive healthcare for the employee at no monthly cost Healthcare benefit covers medical, prescription drug, dental, and vision Personal Time Off (PTO) Policy plus paid holidays Highly competit
Benefits
- Model training & execution: train, execute, and synthesize large-scale physics-based and machine-learning hydrologic models across regional to continental domains.
- apply deep-learning approaches to hydrologic prediction, including tools such as NeuralHydrology and dHBV.
- Strong Python skills, and experience with a deep-learning framework such as PyTorch.
- Experience with machine-learning hydrologic modeling tools such as NeuralHydrology and dHBV, or comparable physics-informed and differentiable modeling approaches.
Company info
- As part of our ongoing growth and expansion, we are seeking a dynamic and experienced Hydrologic Modeler to join our growing team.
- Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities - creatively and effectively.
This listing is sourced directly from Lynker's careers page and normalized into a canonical job model.