Machine Learning Engineer - Remote

Overview

An opportunity to work as a Machine Learning Engineer in an early-stage startup focused on wildfire prevention using predictive models.

In Short

• Design, build, and deploy machine learning models for lightning prediction and wildfire risk assessment.
• Work with large-scale, diverse data sources including real-time weather data and satellite imagery.
• Experiment with advanced model architectures to enhance predictive accuracy.
• Develop real-time data pipelines and alerting systems for wildfire conditions.
• Collaborate with data scientists, software engineers, and environmental scientists.
• 5+ years of experience in machine learning, preferably in environmental applications.
• Expertise in machine learning frameworks like TensorFlow and PyTorch.
• Experience with time-series analysis and computer vision techniques.
• Familiarity with distributed computing frameworks and cloud platforms.
• A strong motivation to apply machine learning for environmental impact.

Requirements

• 5+ years in machine learning, ideally with environmental or geospatial applications.
• Expertise in machine learning frameworks like TensorFlow, PyTorch, or JAX.
• Experience with time-series analysis and computer vision techniques.
• Proven experience in model architecture design and hyperparameter tuning.
• Familiarity with distributed computing frameworks and cloud platforms.
• A strong motivation to apply machine learning for environmental impact.

Benefits

• Opportunity to shape an innovative, mission-driven solution.
• Work in a fast-paced, early-stage startup environment.
• Contribute to critical research in wildfire prevention.