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Machine Learning Geospatial Jobs in San Diego, CA

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$131K - $173K/yr

Required Skills and Experience: * 10+ years of experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer. * Proven experience developing and ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

Required Skills and Experience: * 10+ years of experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer. * Proven experience developing and ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

Required Skills and Experience: * 10+ years of experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer. * Proven experience developing and ...

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How much do machine learning geospatial jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for machine learning geospatial in San Diego, CA is $30.95, according to ZipRecruiter salary data. Most workers in this role earn between $23.99 and $35.96 per hour, depending on experience, location, and employer.

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 are popular job titles related to Machine Learning Geospatial jobs in San Diego, CA?

For Machine Learning Geospatial jobs in San Diego, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Geospatial jobs in San Diego, CA look for?

The top searched job categories for Machine Learning Geospatial jobs in San Diego, CA are:

What cities near San Diego, CA are hiring for Machine Learning Geospatial jobs?

Cities near San Diego, CA with the most Machine Learning Geospatial job openings:

Machine Learning Geospatial jobs near you
Infographic showing various Machine Learning Geospatial job openings in San Diego, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $64,368 per year, or $30.9 per hour.

Sr Machine Learning Engineer

San Diego, CA • On-site

The Marlin Alliance, Inc.
Business Management Consulting • 11 - 50 employees
Learn more about The Marlin Alliance, Inc.external

$110K - $152K/yr

Full-time

Re-posted 23 days ago

Job description

Job Summary:
The Marlin Alliance, Inc. is seeking a talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced machine learning models and algorithms in support of naval applications.
Responsibilities:
• Design, develop, and implement machine learning models and algorithms for naval applications.
• Develop and deploy algorithms, mathematical models, and machine learning models into real-world operational environments.
• Perform data preprocessing, feature engineering, model evaluation, and validation.
• Collaborate with engineers, data scientists, and mission stakeholders to align ML solutions with operational requirements.
• Develop cloud-native ML pipelines using AWS, Azure, Docker, Kubernetes, or equivalent platforms.
• Implement ML solutions using frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Contribute to distributed computing and parallel processing approaches to optimize ML model performance.
• Participate in CI/CD pipeline development, automation, and DevSecOps workflows.
• Apply cybersecurity principles in the design and deployment of machine learning systems.
• Provide documentation, technical reports, and engineering artifacts consistent with PMAT and government standards.
• Stay current with advancements in machine learning, data science, and emerging technologies relevant to naval and DoD applications.
Qualifications:
Required:
• 10+ years of 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.
• Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong programming skills in Java, C++, Go, or Rust.
• Experience with distributed computing and parallel processing.
• Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
• Strong analytical, problem-solving, and communication skills.
• Ability to work effectively in a collaborative team environment.
• Previous experience supporting government agencies or military organizations.
• 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 reoccurring basis during shipboard operations or testing evolutions.
• Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).
• US Citizenship is required.
• No Dual Citizenship.
• Active Secret clearance required; TS SCI clearance highly preferred.
• Bachelor of Science degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or Statistics.
Preferred:
• 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.
• Experience supporting NAVWAR, NIWC Pacific, or other Navy C2/ISR programs.
Company:
The Marlin Alliance, Inc. Founded in 2002, the company is headquartered in San Diego, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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