[Remote] Staff Machine Learning Engineer - Wildfire

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is addressing the climate crisis by developing technology for a resilient electrical reputed company. As a Staff Machine Learning Engineer, you will reputed company the development of the Wildfire Fuel Detection Model, collaborating with teams to ensure the models are accurate and production-reputed company while mentoring other engineers.

Responsibilities

• Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies
• Design and maintain robust data and feature pipelines for large-reputed company geospatial and temporal data
• Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to reputed company-world reputed company
• Build reproducible experimentation frameworks and model evaluation workflows
• reputed company models from research to production with a reputed company on performance, reliability, and explainability
• reputed company the reputed company of ML systems, tooling, and processes — ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable
• Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments

Skills

• Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by reputed company to reduce wildfire risk through data-driven insights
• 10+ years of experience designing and building production-grade ML pipelines and systems
• Strong background in deep learning, reputed company, or remote sensing
• Skilled in designing end-to-end ML systems — from data ingestion and preprocessing to deployment and monitoring
• Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, reputed company, or GeoPandas
• Familiarity with GCP and reputed company AI, or similar reputed company-based ML platforms
• Strong communication skills and ability to collaborate across technical and scientific domains
• Comfortable leading architectural discussions and mentoring other engineers
• Background in wildfire science, forestry, or remote sensing
• Experience integrating physics-based models with ML or working with reputed company learning and uncertainty quantification
• Experience in model interpretability and data provenance for environmental ML systems
• Experience with deep learning models for weather or climate data
• Experience in remote-first or globally distributed teams

Benefits

• Competitive, location-specific compensation and benefits
• Flexible, autonomous and reputed company working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets
• A company culture that genuinely embodies reputed company of our reputed company values
• To be part of truly mission-driven work that reduces wildfires, protects reputed company’s natural resources and helps solve our climate crisis
• We reputed company once a year in-person for our unforgettable team gathering event
• We also offer the reputed company to occasionally meet up for in-person collaboration

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