Staff Software Engineer
Applied Machine Learning
Confirmed live in the last 24 hours

51-200 employees

AI-driven carbon sequestration verification and monitoring
Company Overview
Pachama stands out as a leader in the fight against climate change, leveraging AI and satellite data to facilitate and monitor global carbon sequestration projects. The company's unique approach has earned it a spot in the AI 50, a list recognizing the top 50 most promising AI-based businesses. Pachama's culture is rooted in its mission to restore nature, fostering a work environment that is both purpose-driven and technologically advanced.
AI & Machine Learning
Data & Analytics
Social Impact

Company Stage

Series B

Total Funding





San Francisco, California

Growth & Insights

6 month growth


1 year growth


2 year growth

Experience Level
Desired Skills
Data Science
Data Structures & Algorithms
AI & Machine Learning
Software Engineering
  • Experience tech leading larger cross-team engineering efforts
  • Experience with Machine learning and statistics at scale with an ability to apply these skills to new domains like forest science and remote sensing
  • Strong software engineering practices and a background in Python programming, debugging/profiling, and version control and system design. Some examples of tools in our tech stack include Kubernetes, Dask, Flyte. Open source geospatial tools that are also part of our tech stack include Rasterio, Geopandas, and Xarray
  • Experience working in cluster environments and an understanding of the related distributed systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks, pipelining/multiprocessing, etc)
  • Ability to find and synthesize related academic literature to apply these learnings to model and experiment design
  • Comfort with fast pace execution and rapid iteration startup environment. Excited by product impact
  • Passion for environmental sustainability and a desire to make a meaningful impact on the planet
  • Impact: Building and releasing new algorithms and tools to enable customers to identify and originate the highest quality nature based projects
  • Technical leadership for cross-functional projects. Connect product value with scientific complexity and rigor to develop strategies and vision for the models we need to build and how we build them. Working with teams to implement this vision
  • Innovating by driving core design and ideation of new systems, models and data to leverage to measure the impact of conservation and reforestation projects
  • Hands on contributions coding the systems and tools that enable research and operations to produce high-quality performance metrics for forest carbon projects. Optimizing methods to run efficiently on large amounts of geospatial and remote sensing data
  • Designing statistical frameworks and experiments to assess the quality of these measurements and models on real-world data. The quality of model outputs directly impacts the quality of forest carbon projects
  • Advocating for and mentoring on best practices applied to our AI and data science work. Mentoring teammates to raise the bar across the Protocol teams to enable step-level increases in efficiency, correctness, accuracy, reliability
  • Clearly communicating the impact and learnings from our deep tech crossfunctionally so organizationally we understand how AI and remote sensing can help us find and design better projects