THE MISSION

The climate crisis is accelerating — and with it, the urgency for informed, decisive action. At the heart of our mission is a commitment to transforming complex geospatial and satellite data into clear, actionable intelligence. We empower faster, smarter decisions in the face of wildfires and their cascading environmental, social, and economic impacts.
By building innovative products that integrate machine learning and geospatial science, and operational excellence, we help our partners detect, monitor, and respond to fire-related risks in real time. Our tools are designed not just to observe the world, but to protect it — enabling frontline responders, scientists, and policymakers to act with clarity and confidence when every second matters. The below is just an orientation and successful candidates may not meet all of these criteria.

RELEVANT SKILLS

• 4+ years industry experience in applied Data Science and Machine Learning. 2+ years of industry experience if you have a PhD.

• Expertise in clean code practices and collaborative software development and deployment (e.g. Git, Docker)

• ML Experience across multiple domains (e.g. Computer Vision, Multimodal learning, NLP,…) strongly desired
• A drive for operational excellence and user-centric development workflows.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork abilities.
• Ability to visualize concepts and translate technical insights into business solutions.
• Proactive and results-driven mindset. High adaptability in a fast-paced environment.

Ways to stand out from the crowd:

• Delivered machine learning based products through the whole lifecycle from first prototype to production use
• Previous experience with MLOps tools
• Previous experience with Machine Learning for geospatial data, particularly satellite images
• Previous experience with vision x language models
• Previous experience with fire modeling or fire behavior (Fire detection, fire spread, fire risk, etc.)

• Operational Efficiency: Lead and innovate best practices for operational excellence in geospatial data science. Optimize end-to-end geospatial processes for maximum efficiency and scalability.

• Project, Product & Technical Leadership: Be a go-to expert for machine learning in the company, consult acquisition of complex projects and support product development as technology field expert. Mentor team members.

• Industry Impact: Develop and implement state of the art geospatial technologies (IP, research), collaborating with trusted research partners in academia

Customer Interaction: Work closely with clients to understand their needs, ensuring that data acquisition, processing, and analysis provide significant value from initial engagement through final delivery.