VP Software Engineering at GM Financial responsible for technology implementation strategy and leading product teams in Agile environment. Championing technology modernization and driving operational excellence.
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
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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