Remote Staff ML Engineer - Lead Wildfire Risk ML Systems

CloudDevs; Town of Sweden (NY); On-site; USD 130,000 - 160,000; Full time

Benefits offered by this job

Flexible working environment

Remote working budget

Educational budget

Time to develop new skills

Equity and competitive salary

Job summary

CloudDevs is seeking a Staff Machine Learning Engineer to lead the development of our Wildfire Fuel Detection Model. In this role, you will work with a diverse team to create advanced machine learning models aimed at predicting vegetation and fuel conditions, helping to mitigate wildfire risks.

The ideal candidate has over 10 years of experience, is skilled in deep learning and geospatial data, and thrives in a remote-first environment. You'll enjoy flexible work hours and be part of a mission-driven team dedicated to climate action.

Qualifications

• 10+ years of experience designing and building production-grade ML pipelines and systems.
• Strong background in deep learning, computer vision, or remote sensing.
• Hands-on experience with various ML frameworks and data tools.

Responsibilities

• Lead the development and scaling of Wildfire Fuel Detection Model.
• Architect and build advanced ML models for vegetation mapping.
• Design robust data and feature pipelines for large-scale data.

Skills

Machine learning

Geospatial data

Deep learning

Remote sensing

Software development

Tools

PyTorch

TensorFlow

XGBoost

LightGBM

Dask

Spark

GeoPandas

GCP

Vertex AI

Job description

CloudDevs is seeking a Staff Machine Learning Engineer to lead the development of our Wildfire Fuel Detection Model. In this role, you will work with a diverse team to create advanced machine learning models aimed at predicting vegetation and fuel conditions, helping to mitigate wildfire risks.

The ideal candidate has over 10 years of experience, is skilled in deep learning and geospatial data, and thrives in a remote-first environment. You'll enjoy flexible work hours and be part of a mission-driven team dedicated to climate action.