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Machine Learning Engineer; part-time​/Idaho

Job in Boise, Ada County, Idaho, 83708, USA
Listing for: Pitch Aeronautics Inc.
Part Time position
Listed on 2025-12-23
Job specializations:
  • Engineering
    Data Engineer, AI Engineer, Systems Engineer
Salary/Wage Range or Industry Benchmark: 30 - 50 USD Hourly USD 30.00 50.00 HOUR
Job Description & How to Apply Below
Position: Machine Learning Engineer (part-time / Idaho-based)

Pitch Aeronautics Inc. Machine Learning Engineer (part-time / Idaho-based) Boise,
· Part time Apply for Machine Learning Engineer (part-time / Idaho-based)

We’re seeking a talented Machine Learning Engineer to help us harness weather and environmental data to build better forecasting models.

About Pitch Aeronautics Inc.

Pitch Aeronautics () is a rapidly growing startup creating game-changing solutions for the utility industry. Pitch has developed a drone to install our line sensor, bird diverters, and other equipment on power lines. Our drone-deployable line sensors wirelessly transmit environmental and line characteristics to an online secure API to help utilities push more power through existing lines, prevent wildfires, and improve grid reliability.

At Pitch we’ve fostered a collaborative, fun, “get-stuff-done” working environment. We believe in moving fast and creating products and prototypes rapidly. If you’re looking for a place where you can make a difference on day one, be empowered to achieve, and love working in small teams, we want to meet you!

Description

Company Description

Pitch Aeronautics (  ) 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 line sensors wirelessly transmit real-time environmental and line data to a secure online platform—helping utilities push more power through existing lines, reduce wildfire risk, and improve grid reliability.

We’re seeking a talented Machine Learning Engineer to help us harness weather and environmental data to build better forecasting models and drive smarter grid operations. This role focuses specifically on developing and deploying ML models that analyze weather patterns, forecast conditions along transmission lines, and support real-time decision-making for utility operators.

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 shape next-generation climate-aware energy infrastructure, we’d love to meet you.

Learn more about our company at:

-Our website:

-Our Linked-In posts:

-Our Facebook posts:

-Here’s a video of our drone performing a sensor installation on an energized power line:

Role Description

This is a part-time, on-site role based in Boise, Idaho . As an ML Engineer focused on weather data and forecasting , you will design and deploy machine learning models that improve our ability to predict wind, temperature, solar radiation, and other environmental factors along high-voltage transmission corridors. Your models will power our analytics platform, enabling more accurate Dynamic Line Ratings (DLR) and helping utility companies mitigate wildfire and outage risks.

You’ll work across weather datasets, time-series sensor data, and geospatial models to extract insights that improve operational planning and real-time decision-making.

Responsibilities

  • Develop machine learning models that forecast weather and environmental conditions (wind speed, ambient temperature, solar radiation, etc.) at high spatial and temporal resolution
  • Integrate real-time weather data, forecast models, and sensor data into predictive pipelines that support grid planning and risk analysis
  • Apply time-series analysis, ensemble learning, and probabilistic modeling techniques to generate high-confidence forecasts
  • Work closely with hardware and software teams to ensure models are effectively integrated into our analytics platform
  • Build scalable data pipelines for ingesting, cleaning, and processing weather and IoT sensor data
  • Quantify uncertainty in model outputs and develop confidence intervals for DLR recommendations
  • Collaborate with product managers and utility partners to refine use cases and tailor models to real-world needs
  • Optimize and deploy ML models using AWS tools and cloud infrastructure (e.g., Sage Maker, Lambda, EC2)
  • Document model methodologies, assumptions, and performance for internal and customer use

Minimum Qualifications

  • Bachelor’s or Master’s degree in Computer…
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