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Shapely Jobs (NOW HIRING)

Vantor

Applied Geospatial ML Engineer

Herndon, VA · On-site

... shapely) or equivalent • Experience with a designing and implementing a wide variety of geospatial trajectory processing, analysis (e.g., forecasting), and visualization approaches • Ability to ...

vetegrity

Data Scientist 3

Annapolis Junction, MD · On-site

... g., Plotly, Shapely, GeoPandas, Kibana, Elastic, SQL, Jupyter) - Experience with ETL workflows, batch/incremental data ingestion, and robust error handling - Ability to automate analytic and ...

Planet

Senior Forward Deployed Engineer

OR · Remote

$104K - $143K/yr

Experience with geospatial software development and concepts (e.g., Rasterio, Fiona, Shapely, OpenLayers, GDAL). * AWS or GCP experience. * Proficiency in Python. * Excellent knowledge of software ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site

... Shapely, xarray, or Zarr. • Experience with modern ML infrastructure, including cloud services (e.g., AWS), containerization and orchestration platforms (e.g., Kubernetes), and the ability to adapt ...

GRVTY

Data Scientist, Senior

Chantilly, VA · On-site +1

Experience with geospatial Python libraries such as GeoPandas, Shapely, Rasterio, or GDAL. * Familiarity with NGA data systems, GEOINT product formats, or IC data standards. * Experience deploying ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site

... Shapely, xarray, or Zarr. • Experience with modern ML infrastructure, including cloud services (e.g., AWS), containerization and orchestration platforms (e.g., Kubernetes), and the ability to adapt ...

Vantor

Senior Geospatial Data Engineer

Mclean, VA · On-site

$116K - $139K/yr

... Shapely, Fiona, Rasterio, GDAL, QGIS, or similar geospatial tools and libraries. • Experience building repeatable data pipelines for geospatial data ingestion, processing, validation, and ...

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Shapely information

What are some common challenges faced by software engineers working on the Shapely library, and how can job seekers prepare for them?

Software engineers contributing to the Shapely library often encounter challenges related to geometric algorithms, spatial data precision, and cross-platform compatibility. Debugging complex geometry issues and ensuring robust handling of edge cases require a solid understanding of computational geometry and Python development. Collaboration with GIS professionals and open-source contributors is also a key part of the role, so strong communication skills and experience with open-source workflows are valuable. Familiarity with related libraries like GEOS and understanding spatial data formats can help job seekers excel.

What is a Shapely job?

Shapely jobs typically refer to roles that involve working with the Shapely library, a popular Python package used for manipulation and analysis of planar geometric objects. Professionals in these positions often use Shapely for tasks in geographic information systems (GIS), spatial data analysis, and mapping. Job responsibilities may include developing geospatial applications, processing and analyzing spatial data, and integrating Shapely with other Python libraries such as GeoPandas. These roles are commonly found in industries like urban planning, environmental science, and data analytics. Having strong Python skills and experience with spatial data is usually required.

What are the key skills and qualifications needed to thrive as a Shapely web developer?

To thrive as a Shapely web developer, you need proficiency in web development languages such as HTML, CSS, JavaScript, and familiarity with WordPress, alongside experience with responsive design principles. Knowledge of the Shapely WordPress theme, page builders, plugins, and version control systems like Git is typically required. Strong problem-solving abilities, attention to detail, and effective communication help developers efficiently address client needs and collaborate with teams. These skills ensure the development of attractive, functional, and user-friendly websites that meet client specifications.

What is the difference between Shapely vs GIS Analyst?

AspectShapelyGIS Analyst
Required CredentialsBasic programming knowledge, Python skillsBachelor's degree in Geography, GIS, or related field
Work EnvironmentProgramming, data analysis, scriptingMapping, spatial data analysis, report creation
Industry UsageUsed in GIS software development and data processingApplied in urban planning, environmental management, and more
Common Search IntentData manipulation, spatial analysis in PythonGIS data analysis, mapping projects

Shapely is a Python library for geometric operations and spatial data manipulation, often used by developers and data analysts. GIS Analysts perform broader spatial data analysis, mapping, and reporting within GIS software. While Shapely focuses on geometric calculations, GIS Analysts handle comprehensive spatial projects. Both roles overlap in spatial data handling but differ in scope and tools used.

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What cities are hiring for Shapely jobs? Cities with the most Shapely job openings:
What states have the most Shapely jobs? States with the most job openings for Shapely jobs include:
What job categories do people searching Shapely jobs look for? The top searched job categories for Shapely jobs are:
Shapely jobs near you
Infographic showing various Shapely job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution.

Applied Geospatial ML Engineer

Vantor

Herndon, VA • On-site

Full-time

Re-posted 7 days ago

Job description

Job Summary:
Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what’s happening now and shape what’s coming next. They are seeking an experienced AI/ML engineer to work across the full analytical workflow—from data acquisition and model development to pipeline evaluation, application prototyping, and hardware-based solution implementation.
Responsibilities:
• Contribute to multi-discipline AI/ML engineering teams using multi-INT data (with emphasis on GEOINT) to design, implement, and evaluate machine learning solutions
• Engineer and transform diverse data types to support all phases of the AI/ML workflow
• Architect, develop, and integrate novel AI/ML models (e.g., semantic activity detection, geospatial analytics, signal processing, and computer vision)
• Design, implement, and assess various geospatial AI/ML solutions across hardware and software stacks
• Stay current on AI/ML advances from industry and academia, applying them to government mission challenges
• Provide subject matter expertise, mentoring, and strategic advice to government and internal teams on AI/ML trends, approaches, and delivery strategies
• Communicate progress, results, risks, and challenges to government clients, partners, and project leadership
• Support program execution by integrating diverse data science skillsets, managing sprint projections, assessing risks, and occasionally traveling for meetings and demonstrations
Qualifications:
Required:
• Must be a U.S. citizen with an active TS/SCI and the ability to obtain a CI polygraph.
• B.S. in Data Science, Engineering, Math, Physics, Computer Science, or related field
• 5+ years designing, developing, testing, and deploying AI/ML models across diverse data types
• Minimum 2 years of experience with low-shot learning, robust ML, spatial trajectory analytics, and cloud-based platforms (e.g., AWS, Azure) and AI/ML services (e.g., SageMaker, Watson Studio)
• Experience working with remote sensing and geospatial datasets, including EO/SAR imagery, sensor-based data streams and familiarity with government collection platforms.
• Experience with modern development practices, including version control, and CI/CD
• Strong communication skills demonstrated through technical writing and speaking engagements (e.g., briefings, conference presentations), with excellent organizational skills and attention to detail
• Competence with Linux environments
Preferred:
• Advanced degree (M.S. or Ph.D.) in Data Science, Engineering, Math, Physics, Computer Science, or a related field
• Proficiency with the Python data science stack (e.g., numpy, pandas, matplotlib, sklearn) and geospatial libraries (e.g., gdal, geopandas, shapely) or equivalent
• Experience with a designing and implementing a wide variety of geospatial trajectory processing, analysis (e.g., forecasting), and visualization approaches
• Ability to design and implement compute hardware and infrastructure solutions to support both client and backend AI/ML applications
Company:
A spatial intelligence firm. Founded in 2025, the company is headquartered in Denver, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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