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Machine Learning Geospatial Jobs in Virginia (NOW HIRING)

... time series, geospatial, and imagery data, and must operate under challenging constraints not ... The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ...

... time series, geospatial, and imagery data, and must operate under challenging constraints not ... The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ...

... time series, geospatial, and imagery data, and must operate under challenging constraints not ... The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ...

Do you like working with geospatial intelligence (GEOINT) data? If so, you'll love working with us ... evaluate machine learning solutions * Engineer and transform diverse data types to support all ...

Responsibilities for this position include providing imagery and geospatial analysis services in the Machine Learning disciplines to facilitate the creation, review, and verification of training data ...

Data & Geospatial Standards Specialist

Springfield, VA · On-site

$59K - $72K/yr

... machine learning, artificial intelligence, entity extraction, and automated taxonomy generation ... Systems, Geospatial Science, Computer Science, or related field. • 8+ years of progressive ...

Showing results 41-60

Machine Learning Geospatial information

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What job categories do people searching Machine Learning Geospatial jobs in Virginia look for?

The top searched job categories for Machine Learning Geospatial jobs in Virginia are:

What cities in Virginia are hiring for Machine Learning Geospatial jobs?

Cities in Virginia with the most Machine Learning Geospatial job openings:

Senior Machine Learning Engineer

STR

Arlington, VA

$155K - $195K/yr

Full-time

Re-posted 21 days ago


Job description

About the Team:

STR's Intelligence Division researches and develops advanced analytics and machine learning-based solutions to solve challenging problems related to national security. Our team consists of passionate and motivated engineers with advanced degrees in engineering, computer science, mathematics, and data science, who are seeking opportunities to use their deep technical knowledge and creativity to tackle some of the hardest problems that our customers face. Our projects span multiple different data modalities and incorporate advanced algorithms, deep learning, and statistical techniques to uncover patterns in social media, structured and unstructured text, time series, geospatial, and imagery data, and must operate under challenging constraints not typically found in the commercial world. The tools and technologies we develop have real world impact and US Government analysts and operators use them to enable intelligence activities around the globe.

The Role

As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into production systems that solve critical national security problems.

Working as part of a multidisciplinary team of researchers, engineers, and domain experts, you will bridge the gap between prototype and product by hardening solutions, building scalable backend services, and creating polished user interfaces with intuitive workflows. You will build software with AI/ML at its core, ranging from classical statistical methods to frontier language models, deployed across a diverse set of platforms including cloud, onprem, desktop, mobile, and edge devices. In addition, you will collaborate closely with customers to understand mission needs, rapidly prototype capabilities, and iterate based on user feedback.

What You'll Do:

  • Partner directly with customers, stakeholders, and end users to translate mission needs into technical requirements and iterate based on real-world feedback
  • Drive technical excellence by providing leadership and championing software engineering best practices across multidisciplinary teams
  • Architect loosely coupled systems prioritizing interpretability, maintainability, and feature growth
  • Bridge the gap between research and production by implementing novel capabilities into existing live systems
  • Engineer robust backend services, scalable APIs, and optimized database models
  • Develop polished, intuitive, and responsive user interfaces in close collaboration with UI/UX designers
  • Orchestrate the deployment and maintenance of applications across cloud, desktop, mobile, and edge environments, including air-gapped systems
  • Build and optimize CI pipelines and manage execution runners to maintain code quality and reproducible builds
  • Contribute to the full software development lifecycle, including strategic project planning, rigorous code reviews, and comprehensive testing

Who you are:

  • Active Secret security clearance, for which U.S citizenship is needed by the U.S government
  • Enjoys working hard and seeing mission impact
  • BS degree in Computer Science, Software Engineering, Data Science, Statistics, Mathematics, Physics, or a related technical field
  • 6+ years of professional software engineering and/or machine learning research experience (or equivalent experience depending on degree)

Soft skills

  • Strong written and verbal communication skills, with the ability to explain complex technical concepts to both technical and nontechnical audiences
  • Demonstrated ability to collaborate effectively within crossfunctional teams, give and receive constructive feedback, and mentor others
  • Comfortable building from partial or ambiguous requirements and iterating quickly based on user feedback and changing mission needs

Technical Skills

  • Experience developing, training, and deploying machine/statistical learning models using modern Pythonbased frameworks
  • Experience running models on NVIDIA GPUs
  • Experience containerizing and deploying software using Docker, and on cloud platform
  • Experience designing and implementing REST APIs
  • Experience designing data models and working with relational databases
  • Fluency in Python and its ecosystem
  • Proficiency in at least one systemslevel language with manual or lowlevel memory management
  • Proficiency in HTML, CSS, and JavaScript (experience with a modern frontend framework such as Svelte or React is a plus)
  • Solid understanding of software engineering principles, including testing, scalability, observability, maintainability, and performance optimization

Pay Information
Full-Time Salary Range: $155,000 - $195,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate's experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.