[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, computer 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 core 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
reputed company