Senior Geospatial Machine Learning Engineer
J
JobgetherClimate Technology
UKFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8–10+ years
- Required Skills
- PythonMachine LearningPyTorchTensorflowDeep Learning
Requirements
- 8–10+ years of experience in machine learning engineering, geospatial engineering, remote sensing, or a closely related technical field.
- Strong Python programming skills with hands-on experience using geospatial libraries such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas.
- Experience with scientific Python tools including NumPy, SciPy, scikit-learn, and Pandas.
- Practical experience developing deep learning solutions using frameworks such as PyTorch and/or TensorFlow.
- Strong understanding of satellite imagery, aerial imagery, and geospatial raster/vector data processing.
- Experience with workflow orchestration tools such as Dagster or similar platforms.
- Ability to independently lead initiatives, manage technical projects, and communicate results effectively.
- Passion for climate technology and using machine learning to address complex environmental problems.
Responsibilities
- Develop new geospatial intelligence products using Python-based geospatial libraries, machine learning, and deep learning techniques.
- Improve existing solutions through data exploration, model optimization, debugging, and performance enhancements.
- Work with satellite and aerial imagery, raster and vector datasets, and geospatial workflows to solve real-world challenges.
- Lead technical projects from planning and experimentation through implementation, delivery, and stakeholder communication.
- Build tools and processes to evaluate model performance, product impact, and data-driven prioritization.
- Collaborate with data engineering, product, platform, and delivery teams throughout the full machine learning product lifecycle.
- Contribute to technical direction, engineering practices, and team culture within a fast-growing environment.
- Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
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