Software Engineer (ML Systems)

Our growing team is looking for an experienced and motivated software engineer (mid-level or senior) to help us scale our technical infrastructure and analytical products for soil carbon quantification. This role builds on and expands our ML and geospatial systems, taking ownership of core ML workflows and pipelines, while also supporting the evolution of our backend and cloud infrastructure. You will be responsible for building robust and scalable systems that power our MRV tools, helping us deliver trustworthy and impactful climate solutions.

We're looking for someone with strong software engineering skills, a background in ML- and data-intensive systems, and an interest in geospatial or environmental data. You will join a cross-functional, mission-driven team working to bring transparency and integrity to climate action. We value proactivity, authenticity, empathy and solution mindset in our company culture.

Preferred start date: As soon as possible Vacation days: 30 days PTO Perk: 500,00 € training budget to use for your professional self-improvment, flexible and hybrid work environment Type of Employment: Full-time, unlimited contract

Tasks

• Own and improve our ML training and evaluation pipelines, making them more reliable, flexible, and easier to extend
• Improve configuration, maintainability, and traceability of our ML workflows (e.g., parameter handling, experiment tracking, pipeline design)
• Reduce complexity and improve reliability in our Google Earth Engine (GEE) feature pipeline
• Contribute to the development of our geospatial data infrastructure, extending our capacity to store and process vector files, as well as high-resolution raster datasets
• Own and improve our CI/CD and testing strategy, supporting integration tests, dependency upgrades, and stronger release hygiene
• Support with further development of our GCP infrastructure, adapting our architecture, monitoring and access management to evolving needs

• A degree in Software Engineering, Computer Science, or a related field, with strong foundational knowledge in software development
• 3+ years (mid-level) or 5+ years (senior) of experience in engineering roles building backend applications and pipelines for data- or ML-intensive systems
• Full proficiency in Python, solid knowledge of SQL, and working knowledge of orchestration tools such as Airflow
• Experience with production ML systems, including training and evaluation pipelines, and collaboration with data scientists
• Familiarity with cloud platforms (ideally GCP), including infrastructure-as-code, IAM, and system monitoring
• Strong experience in software development lifecycle and operations (version control, testing, CI/CD)
• A strong sense of ownership and ability to work independently in a fast-paced, collaborative environment, comfortable navigating ambiguity and evolving priorities
• Clear communication and a readiness to take initiative in technical design discussions
• Motivation to contribute to climate action and sustainable development through a rapidly evolving technology space, * Experience building/maintaining MLOps pipelines using state-of-the-art tools, incl. model deployment, versioning and performance tracking
• Experience working with raster data and/or geospatial pipelines in production environments
• Exposure to Google Earth Engine (GEE) or large-scale feature pipeline systems
• Previous exposure to earth observation, environmental monitoring or soil science data

• Be part of our highly motivated, committed, and international team with flat hierarchies that is working on solving one of societies' biggest challenges: Climate change
• Witness and shape the evolution of a new business being built
• Collaborative engineering culture with opportunities for continuous learning and improvement
• Work in a casual environment with flexible hours and some ability to work from home
• Competitive salary, benefits, and compensation package
• Drinks, snacks, team events, and your choice of hardware

Seqana is a start-up building digital monitoring, reporting, and verification (MRV) tools using remote sensing and AI to drive soil carbon sequestration and support the transition towards regenerative, climate-preserving agriculture at scale. We are backed by venture capital investors and supported by public funding from ESA and DLR. Capturing carbon in soils through regenerative agricultural practices is a powerful and still underutilized solution to climate change, with significant co-benefits including improved soil health, water quality, food security, and biodiversity. Existing MRV solutions for soil carbon are a major driver of cost and complexity in carbon projects and often limit scalability. At Seqana, we combine satellite imagery, an extensive proprietary library of soil datasets, and machine learning to deliver an accurate, cost-effective, and scalable MRV solution for soil organic carbon. Our product enables project developers, agrifood corporations, NGOs, and government entities to credibly measure, quantify, and report the climate impact of regenerative agricultural practices.