Pitch Aeronautics Inc. Atmospheric Scientist (Modeling & Meteorology) Remote · Full time

Apply for Atmospheric Scientist (Modeling & Meteorology)

Company Description

Pitch Aeronautics (www.pitchaero.com) is a rapidly growing startup creating game-changing solutions for the utility industry. We’ve developed a drone to install our innovative line sensor, bird diverters, and other equipment directly onto power lines. Our drone-deployable WireWarrrior line sensors wirelessly transmit real-time environmental and line data to our secure WireWeather software to help utilities push more power through existing lines, reduce wildfire risk, and improve grid reliability.

We’re seeking a talented Atmospheric Scientist to help us harness atmospheric data—particularly boundary layer meteorology—to develop and refine forecasting models that drive smarter grid operations. This role focuses specifically on understanding boundary layer processes, deploying numerical models, and integrating results into our line rating and risk mitigation platform.

At Pitch, we’ve fostered a collaborative, fun, “get-stuff-done” work environment. We move fast, prototype quickly, and empower team members from day one. If you want to help shape next-generation climate-aware energy infrastructure, we’d love to meet you.

Learn more about our company at:

• Our website
• Our LinkedIn page
• Video of our drone installing WireWarrior weather stations on transmission lines

Role Description

This is a full-time, hybrid role based in Boise, Idaho. As an Atmospheric Modeling & Meteorology Engineer/Scientist, you will leverage your background in atmospheric physics (especially boundary layer meteorology) to develop, refine, and operationalize weather and environmental models that provide high-resolution stochastic wind and temperature forecasts. These forecasts are used to enhance dynamic line ratings and wildfire/outage risk mitigation for utility companies. You’ll be responsible for integrating real-world sensor data, meteorological datasets, and numerical weather prediction outputs (including CFD models like WindNinja) to improve our AI/ML models for localized weather prediction.

Responsibilities

• Develop and refine AI/ML atmospheric models focused on boundary layer physics, wind flow, temperature profiles, and terrain.
• Adapt and integrate numerical weather prediction (NWP) and physics-based models (e.g., WRF, WindNinja, or similar) for AI/ML training and localized forecasting along power lines
• Work with national/international weather models and real-time weather sensor data to assimilate boundary layer observations and improve predictive accuracy
• Collaborate with data science and ML teams to merge physics-based models with machine learning approaches, enhancing forecast reliability and spatiotemporal resolution
• Evaluate model weather predictions to identify forecast skill and provide direction on model improvements.
• Validate and calibrate models against ground truth data, quantifying uncertainty and providing confidence intervals for operational decisions
• Quantify and address sources of model and data uncertainty, developing robust data assimilation and error-correction strategies to enhance forecast reliability.
• Ensure data quality from custom sensors measuring ambient conditions and third-party weather data sources, working closely with hardware engineers, software engineers, third-party support. Employ quality-control procedures to improve sensor accuracy and reliability.
• Provide inputs to WireWarrior sensor engineers to improve the next generation of drone-deployed weather/powerline sensors.
• Communicate findings and recommendations to data scientists, engineers, utility partners, and internal team.
• Document methodologies and results, ensuring clarity for stakeholders and long-term maintainability

Minimum Qualifications

• Master’s or Doctoral degree in Atmospheric Science, Meteorology, Physics, or a related field
• In-depth understanding of boundary layer meteorology, atmospheric physics, or related disciplines
• Experience with numerical weather prediction models (e.g., WRF, CFD, etc) or other atmospheric modeling frameworks
• Proficiency in time-series analysis and working with large environmental datasets
• Strong analytical and problem-solving skills, with an ability to quantify and communicate forecast uncertainty
• Familiarity with modern computing environments (e.g., Java/Python for data processing, HPC/cloud resources for large-scale model runs)
• Must be a U.S. citizen or lawful permanent resident 

Desired Qualifications

• Experience with boundary-layer wind models or CFD frameworks such as WindNinja
• Field observations of weather data and improvement of field sensors.
• Prior work with NOAA datasets, wind/solar irradiance models, or relevant climate data sources
• Background in energy systems or utility sector operations, especially around transmission line rating and wildfire risk