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Arcgis Machine Learning Jobs (NOW HIRING)

Lumen Solutions Group Inc.

ArcGIS Architect

Austin, TX · On-site

$62.50 - $82.25/hr

... machine learning and LLMs for data extraction, cleaning, and documentation. • Experience with GeoAI for spatial data analysis and prediction and/or generative AI to enhance geospatial analytics ...

WGI

Intern - Geospatial AI Fall 2026

Huntsville, AL

Familiarity with GIS platforms such as ArcGIS Pro, QGIS, or similar * Experience working with geospatial data libraries (e.g., GDAL, rasterio, geopandas) * Exposure to machine learning libraries such ...

kgs

Data Scientist

Cape Canaveral, FL

The ideal candidate will leverage advanced analytics, machine learning, and geospatial analysis ... ESRI ArcGIS suite of commercial software components * ArcGIS Runtime * ArcGIS Engine * ArcGIS ...

kgs

Data Scientist

Cape Canaveral, FL · On-site

The ideal candidate will leverage advanced analytics, machine learning, and geospatial analysis ... ESRI ArcGIS suite of commercial software components * ArcGIS Runtime * ArcGIS Engine * ArcGIS ...

Koniag, Inc.

Data Scientist

Stennis Space Center, MS · On-site

The ideal candidate will leverage advanced analytics, machine learning, and geospatial analysis ... ESRI ArcGIS suite of commercial software components * ArcGIS Runtime * ArcGIS Engine * ArcGIS ...

Esri

Sr. Software Development Engineer - Gen AI

Redlands, CA · On-site

$123K - $162K/yr

... the ArcGIS platform. In this role, you will design and develop the software used by a large ... Responsibilities : • Develop Python-based machine learning components that enhance how users ...

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Arcgis Machine Learning information

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How much do arcgis machine learning jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for arcgis machine learning in the United States is $21.33, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $22.84 per hour, depending on experience, location, and employer.

What is ArcGIS Machine Learning?

ArcGIS Machine Learning refers to the integration of machine learning techniques with ArcGIS, Esri's geographic information system software. It enables users to analyze spatial data, identify patterns, and make predictions using tools like classification, clustering, and regression within the ArcGIS platform. These capabilities help solve complex geographic problems in fields such as urban planning, environmental science, and resource management. ArcGIS provides both built-in machine learning tools and supports integration with open-source frameworks like scikit-learn and TensorFlow.

What are the key skills and qualifications needed to thrive as an ArcGIS Machine Learning specialist?

To thrive in ArcGIS Machine Learning, you need expertise in geographic information systems (GIS), spatial analysis, data science, and a background in computer science, statistics, or geography. Familiarity with ArcGIS software, Python programming, and machine learning libraries such as scikit-learn or TensorFlow is typically required, along with certifications like Esri Technical Certification. Strong problem-solving skills, attention to detail, and effective communication enable you to interpret complex spatial data and convey insights to diverse stakeholders. These skills are essential for leveraging geospatial data to generate actionable intelligence and support data-driven decision-making.

How do ArcGIS Machine Learning professionals typically collaborate with GIS analysts and data scientists within a project team?

ArcGIS Machine Learning professionals often work closely with GIS analysts to prepare and preprocess spatial data, ensuring datasets are clean and relevant for modeling. They also partner with data scientists to design, implement, and validate machine learning algorithms tailored to geospatial problems, such as predictive mapping or spatial pattern detection. Regular collaboration occurs through project meetings, code reviews, and joint presentations to stakeholders, fostering a multidisciplinary approach that leverages both spatial expertise and advanced analytics. This teamwork ensures solutions are both scientifically robust and operationally effective.

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

AspectArcgis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related field; knowledge of machine learningBachelor's in Geography, GIS, or related field; GIS certifications often preferred
Work EnvironmentData science teams, GIS departments, tech-focused projectsUrban planning, environmental management, mapping projects
Industry UsageAdvanced spatial data analysis, predictive modelingMapping, data management, spatial analysis
Common Search/ComparisonYesYes

Arcgis Machine Learning specialists focus on applying machine learning algorithms to spatial data for predictive insights, often working with large datasets and programming. GIS Analysts perform spatial data analysis, mapping, and data management, typically using GIS software. While both roles require GIS knowledge, Arcgis Machine Learning emphasizes data science and programming skills, whereas GIS Analysts focus on spatial analysis and visualization.

What other helpful pages are available for Arcgis Machine Learning?

Other pages related to Arcgis Machine Learning:

Infographic showing various Arcgis Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $44,363 per year, or $21.3 per hour.

Senior Machine Learning Engineer

San Diego, CA • On-site

The Marlin Alliance
Business Management Consulting • 11 - 50 employees
Learn more about The Marlin Allianceexternal

$130K - $171K/yr

Full-time

Re-posted 17 days ago

Job description

The Marlin Alliance, Inc. is seeking a Senior Machine Learning Engineer to design, develop, and implement advanced machine learning models and algorithms in support of naval applications. This role requires deep technical expertise in modern machine learning methods, distributed systems, cloud-native development, and software engineering best practices. The Senior ML Engineer will collaborate with multidisciplinary teams to deliver mission-focused AI solutions that integrate into operational Navy environments.
Incorporated in 2002, The Marlin Alliance is a digital transformation company dedicated to ensuring our clients compete and win in tomorrow's digital world. We specialize in creating technical solutions that allow for seamless execution of automated business processes and the generation of governed, machine-consumable data. From strategic planning to advanced analytics and cybersecurity, our team provides cutting-edge, cross-disciplinary solutions. We are seeking motivated professionals who share our agile, solution-oriented mindset and are ready to deliver the real, practical results relied upon by our clients.
Citizenship and Clearance requirements:
  • U.S. Citizenship required
  • No dual citizenship
  • Active TS security clearance required
  • Active TS SCI security clearance preferred

Location - ON-Site near one of the following locations:
  1. 1st Space Brigade - Fort Carson, CO
  2. Air Force TENCAP - Colorado Springs, CO
  3. NIWC LANT - Charleston, SC
  4. Buckley Space Force Base - Denver, CO
  5. NAVWAR - San Diego, CA

Travel:
  • 15%

Responsibilities:
  • Collaborate with cross-functional teams to understand and address Navy operational challenges using data pipelines and analytics.
  • Design, develop, and implement data pipelines and analytics for naval applications.
  • Perform exploratory data analysis, algorithm development, and testing.
  • Normalize and structure data to common standards for interoperability.
  • Work with multiple data formats, including CSV, JSON, XML, Parquet, and ORC.
  • Develop and deploy data pipelines and analytics in real-world operational environments.
  • Deploy, monitor, and optimize data pipelines to ensure high performance and reliability.
  • Implement event streaming pipelines using Apache Kafka, AWS Kinesis, RabbitMQ, or ZeroMQ.
  • Utilize distributed computing platforms such as AWS Lambda, Dask, or Spark.
  • Leverage cloud-native tools including AWS S3, RDS, EFS, SNS, and SQS.
  • Utilize data pipeline frameworks such as AirByte, Apache Airflow, dbt, Apache Iceberg, and Snowflake.
  • Work with GIS data using ArcGIS, PostGIS, and related tooling.
  • Implement containerized environments using Docker or Kubernetes.
  • Apply cybersecurity principles in the context of secure DoD data applications.
  • Communicate findings and engineering solutions effectively with technical and mission stakeholders.

Required Skills and Experience:
  • Experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer.
  • Proven experience developing and deploying algorithms, mathematical models, or machine learning models in real-world applications.
  • Strong programming skills in Python.
  • Familiarity with cloud platforms (e.g., AWS, Azure) or containerization technologies (e.g., Docker, Kubernetes).
  • Familiarity with software engineering best practices, including Git.
  • Strong programming skills in Java, C++, Go, or Rust.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work effectively in a collaborative team environment.
  • Ability to safely carry tools, equipment, and materials aboard ship, including ascending and descending shipboard ladders(stairwells) and navigating confined spaces while maintaining required points of contact. Tools and equipment will weigh no more than 50 lbs.
  • Ability to perform required work aboard Navy vessels and in shipboard environments, including navigating narrow passageways, ascending and descending ladders (stairwells), working on elevated platforms, and operating in variable sea conditions.
  • Ability to perform activities on a recurring basis during shipboard operations or testing evolutions.
  • Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).
  • Candidates should be prepared to complete a coding exercise as part of the interview process.

Preferred Skills and Experience:
  • Experience with distributed computing and parallel processing.
  • Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
  • Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with cloud-native architecture and software API design.
  • Experience integrating machine learning into operational DoD systems or edge computing environments.
  • Familiarity with DoD AI strategies, MLOps, or data engineering in secure environments.
  • Previous experience supporting government agencies or military organizations. (NAVWAR, NIWC Pacific, or other Navy C2/ISR programs strongly preferred).

Education and Certification Requirements:
  • Bachelor of Science in Computer Science, Data Science, Geography, Math, Machine Learning, or Statistics, OR Equivalent years of relevant experience in lieu of a degree
  • Additional certifications in cloud, data engineering, GIS, or cybersecurity are a plus

Job Classification:
Associate II
$110,000 - $180,000
Disclaimer:
This job description in no way states or implies that these are the only duties to be performed by the employee(s) incumbent in this position. Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities.
To perform this job successfully, the incumbents will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities.
This document does not create an employment contract, implied or otherwise, other than an �at-will� relationship.
An Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

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