Machine Learning Engineer

ML Engineer / MLOps role:

My client is tackling a major environmental challenge: global ecosystem restoration. They are developing innovative solutions for nature credits and seek a skilled engineer to join their mission. Their team combines expertise in ecology and machine learning to address complex conservation issues.

Key Responsibilities

• Develop and refine machine learning models using remote sensing and geospatial data.
• Design and conduct tests to ensure model accuracy and reliability.
• Collaborate with scientists to align tech solutions with environmental goals.
• Apply causal inference and Bayesian methods to evaluate carbon projects.
• Engage in collaborative coding and code reviews.
• Stay current with advancements and integrate them into projects.
• Mentor peers on best practices in machine learning and software development.

What They’re Looking For

• Strong commitment to environmental conservation.
• Proficiency in machine learning, Python, and frameworks like PyTorch.
• Experience with geospatial tools such as Rasterio and Geopandas.
• Knowledge of causal inference and Bayesian statistics.
• Familiarity with remote sensing data, including optical and radar imagery.
• Expertise in cloud platforms (e.g., Google Cloud, AWS) and MLOps.
• Adaptable, curious, and skilled in communication.
• Experience working effectively in a remote, diverse team.

For more information, don't hesitate to go out!