Hybrid Software Engineer – ML, Mid-Level/Senior

at Seqana

• Job title: Software Engineer – ML, Mid-Level/Senior
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, Cloud, Google Cloud Platform, Python, SQL
• Location requirements: Hybrid, Berlin, Germany

About the role

• Software Engineer (ML) responsible for enhancing ML workflows in a climate-focused startup. Join Seqana to contribute to innovative solutions for soil carbon monitoring through technology.

Responsibilities

• 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

Requirements

• 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.

Benefits

• 30 days PTO
• 500,00 € training budget
• flexible and hybrid work environment