Senior Geospatial Machine Learning Engineer

Triwill Group; Spain (TX); On-site; USD 81,000 - 127,000; Full time

Benefits offered by this job

Fully remote

Impactful climate projects

Influence technical direction

International team

Cutting-edge ML/Geo tech

Professional growth

Job summary

Jobgether, partnering with a Spain-based team, seeks a Senior Geospatial Machine Learning Engineer to develop AI solutions that transform satellite and environmental data into actionable insights.

You will own projects from experimentation through production, collaborating with data engineering, product, platform, and delivery teams to deliver geospatial intelligence solutions for climate and infrastructure challenges.

Qualifications

• 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.

Skills

Python

Geospatial libraries

NumPy SciPy scikit-learn Pandas

Deep learning frameworks

Dagster

Project leadership

Communication

Climate technology passion

Tools

GDAL

Rasterio

Shapely

Fiona

GeoPandas

PyTorch

TensorFlow

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Geospatial Machine Learning Engineer based in Spain.

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights.

This role sits at the intersection of machine learning, geospatial technology, and climate innovation, helping solve complex challenges impacting critical infrastructure.

You will work on building and improving algorithms that analyze vegetation, assess risks, and support smarter decision‑making for energy systems.

The position offers the opportunity to own impactful projects from experimentation through production while collaborating with multidisciplinary engineering and scientific teams.

You will contribute to the evolution of data‑driven products using cutting‑edge ML techniques, remote sensing data, and geospatial technologies.

This is an ideal opportunity for an experienced engineer passionate about applying AI to create meaningful environmental impact.

Accountabilities

The Senior Geospatial Machine Learning Engineer will design, develop, and improve machine learning solutions that leverage geospatial data to deliver innovative environmental intelligence products. This role requires strong technical ownership, collaboration, and the ability to translate complex data challenges into practical solutions.

• 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.

Requirements

The ideal candidate is an experienced machine learning or geospatial engineer with strong expertise in Python, scientific computing, and applied AI. They should be comfortable working independently, leading projects, and applying advanced technology to environmental and infrastructure challenges.

• 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.

Nice‑to‑have qualifications

• Experience with vegetation science, forestry, energy infrastructure, or utility‑related technologies.
• Familiarity with observability tools such as Sentry and Grafana.
• Previous experience in climate tech, geospatial AI, remote sensing, or environmental data companies.

Benefits

• Fully remote work environment with flexibility across eligible locations.
• Opportunity to work on impactful climate technology projects using AI and satellite data.
• Ability to influence technical direction, processes, and product development within a growing organization.
• Collaboration with a diverse international team across engineering, product, design, and platform functions.
• Exposure to cutting‑edge machine learning, geospatial technologies, and real‑world applications.
• Inclusive culture focused on solving meaningful problems through technology.
• Opportunity for professional growth in a mission‑driven environment.