Join Pachama as a Senior Machine Learning Engineer, Geospatial

Who We Are
Pachama is a mission-driven company dedicated to restoring nature to combat climate change. We employ state-of-the-art remote sensing and artificial intelligence technologies in the realm of forest carbon to scale up forest conservation and restoration efforts. Our innovative technology integrates satellite imagery with AI to measure carbon sequestration in forests. Through the Pachama marketplace, we connect responsible businesses and individuals with carbon credits from projects focused on preserving and restoring forests globally.

We are supported by mission-aligned investors including Breakthrough Energy Ventures, Amazon Climate Fund, Chris Sacca, Saltwater Ventures, and Paul Graham.

Recent Press

• Pachama is the #1 most innovative AI company
• Featured in Jeff Bezos' Last Shareholder Update
• Pachama to monitor and manage Mercado Libre forest projects

Role: Senior Machine Learning Engineer, Geospatial

We are seeking a Senior Machine Learning Engineer to spearhead the development of advanced systems to further our mission of restoring nature and addressing climate change. As a leader on our Science team, you will innovate, scale, and deploy AI and remote sensing technologies to develop products that identify and support high-quality forest carbon projects.

A typical day in this role involves implementing new machine learning models utilizing remote sensing and geospatial data, designing and conducting experiments to validate their performance, engaging in pair coding with fellow engineers, and discussing experimental plans and outcomes with scientists. The accuracy of model outputs is crucial for the success of forest carbon projects, making model validation and uncertainty quantification core values for our team. Staying updated with insights from scientific literature and commercial applications is essential to this role.

We are looking for engineers who are passionate about building, enjoy seeing the end-to-end impact of their work, and motivate their peers. Successful candidates will push initiatives forward by asking insightful questions, overcoming ambiguity, and organizing efforts to achieve results. They will be meticulously detail-oriented and methodical, placing a strong emphasis on rapid development.

Location

This role is remote, available within North American time zones only.

Responsibilities

• Train machine learning models to estimate forest structure parameters critical for quantifying ecosystem carbon storage and evaluating the climate benefits of forest carbon projects.
• Collaborate with the Product team to ensure alignment between product value and scientific and technical complexity.
• Advocate for and mentor on best practices in AI and data science.
• Mentor team members to elevate efficiency, accuracy, and reliability across the Science and Engineering teams.
• Design statistical frameworks and experiments to assess the accuracy and uncertainty of models on real-world data.
• Optimize models to efficiently handle large volumes of geospatial and remote sensing data.
• Develop tools that enable high-quality performance metrics for forest carbon projects.
• Communicate the impact and lessons from our technical work to ensure organizational understanding of how AI and remote sensing can enhance project design and selection.

Requirements

• Strong foundation in machine learning and statistics, with the ability to apply these skills to forest science and remote sensing.
• Experience in deploying deep learning models at scale using distributed computing.
• Proficient in software engineering practices and Python programming. Familiarity with tools such as Kubernetes, Dask, and Flyte is essential. Experience with open-source geospatial tools like Rasterio, Geopandas, and Xarray is a plus.
• Experience in cluster environments and an understanding of distributed systems concepts, including CPU/GPU interactions, latency/throughput bottlenecks, and multiprocessing.
• Proven experience working with LiDAR datasets for vegetation structure analysis.
• Experience handling terrestrial ecosystem geospatial data, including land cover, ecosystem classifications, and biophysical data.
• Knowledge of Landsat, Sentinel 1 and 2, high-resolution imagery (e.g., NAIP, Planet), and harmonizing images across optical sensors.
• Ability to review and synthesize academic literature to inform model and experiment design.
• Comfortable working in a fast-paced startup environment with rapid iteration and execution. Excited by product impact.

Join Pachama and contribute to innovative solutions addressing climate change through forest conservation and restoration