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