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Gis Machine Learning Jobs (NOW HIRING)

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $224K/yr

Develop machine learning models for geospatial inference of key ecosystem metrics, leveraging ... Experience with GIS tools and remote sensing technologies for geospatial analysis. * Prolific ...

Mclaurin Aerospace

GIS Developer

Houston, TX · On-site

Employ GIS and remote sensing techniques to Earth, Moon, and other planetary image data in support ... Machine learning, deep learning, neural networks * Mission science integration and operations

Mclaurin Aerospace

GIS Developer

Houston, TX · On-site +1

Employ GIS and remote sensing techniques to Earth, Moon, and other planetary image data in support ... Machine learning, deep learning, neural networks * Mission science integration and operations

Mclaurin Aerospace

GIS Developer

Houston, TX · On-site

Employ GIS and remote sensing techniques to Earth, Moon, and other planetary image data in support ... Machine learning, deep learning, neural networks * Mission science integration and operations

Esri

GIS Solution Engineer - Water

Philadelphia, PA · On-site

Job Summary : Esri is a leading company in GIS technology, seeking a GIS Solution Engineer ... machine learning concepts • Programming and scripting experience with languages such as Python ...

Esri

GIS Solution Engineer - Defense

Vienna, VA

Experience incorporating real-time information streams with existing GIS data and IT infrastructure * Basic understanding of artificial intelligence/machine learning concepts * Programming and ...

Esri

GIS Solution Engineer - Water

Philadelphia, PA · On-site

Experience incorporating real-time information streams with existing GIS data and IT infrastructure * Basic understanding of artificial intelligence/machine learning concepts * Programming and ...

Esri

GIS Solution Engineer - Defense

Washington, DC · On-site

Esri is a leader in GIS technology, and they are seeking a GIS Solution Engineer for their Defense ... machine learning concepts • Programming and scripting experience with languages such as Python ...

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Gis Machine Learning information

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How much do gis machine learning jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for gis machine learning in the United States is $28.52, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $33.65 per hour, depending on experience, location, and employer.

What are GIS Machine Learning jobs?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are some common challenges faced when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

What are the key skills and qualifications needed to thrive as a GIS Machine Learning Specialist, and why are they important?

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

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

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

More about Gis Machine Learning jobs
What cities are hiring for Gis Machine Learning jobs? Cities with the most Gis Machine Learning job openings:
What states have the most Gis Machine Learning jobs? States with the most job openings for Gis Machine Learning jobs include:
What job categories do people searching Gis Machine Learning jobs look for? The top searched job categories for Gis Machine Learning jobs are:
Gis Machine Learning jobs near you
Infographic showing various Gis Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution, with an average salary of $59,329 per year, or $28.5 per hour.
Machine Learning Research Engineer

Machine Learning Research Engineer

Oxman

New York, NY • On-site

$142K - $224K/yr

Full-time

Posted 18 days ago

Job description

OXMAN
OXMAN is a nature-based research and design company based in Manhattan. We incubate ventures and technologies that reimagine the relationship between humanity and the natural world. Working across disciplines-from architecture and ecology to materials science and computation, we develop nature-centric solutions to critical environmental challenges.
EDEN
Nature provides humanity with services that are critical for survival: the sequestration of carbon, the filtration of water, and the production of the air we breathe. EDEN works to strengthen and regenerate these natural processes by cultivating biodiverse, resilient ecosystems that sustain life for all species-human and non-human alike.
EDEN is a digital design environment for engineering and designing ecosystems, modeling the flows, relationships, and processes that sustain them. We build tools that quantify how landscapes can be engineered to achieve specific performance goals, cooling cities, filtering water, sequestering carbon, and protecting key species, and use them to guide the design of ecologically active sites.
One hectare of well-designed landscape can sequester up to four times the annual emissions of an average home, filter enough water to support thirteen neighborhoods, and reduce ambient temperatures by more than ten degrees. EDEN enables designers to plan intentionally for these outcomes through analysis, simulation, and optimization, turning ecological function into an actionable design parameter.
Our design team works directly with clients to apply these tools toward site-specific goals, from logistics campuses and residential communities to rewilding and climate-resilient developments. Together with our clients, we are designing biodiverse, productive environments that serve both humanity and nature.
Key Responsibilities
  • Develop machine learning models for geospatial inference of key ecosystem metrics, leveraging geospatial AI to synthesize environmental data into actionable parameters for ecosystem design and simulation.
  • Develop and refine advanced deep generative models and reinforcement learning algorithms for built-environment design.
  • Contribute to decision-making frameworks that combine procedural generation with ML and data-driven optimization.
  • Collaborate with computational ecologists and data scientists to integrate generative design with ecosystem simulation models.
  • Align design outputs with ecological performance indicators such as species richness and carbon sequestration.
  • Prepare detailed technical documentation and contribute to model validation using empirical ecological data.

Key Goals and Outcomes
  • Research and development of high-fidelity Geospatial AI models for the automated inference of ecosystem metrics across varied scales.
  • Utilize inferred geospatial data to drive the computational synthesis and design of functional, resilient ecosystems.
  • Establish a robust pipeline for integrating remote sensing and geospatial data into generative design workflows.
  • Deliver scalable ML frameworks that provide real-time or near-real-time feedback on ecological performance (e.g., carbon sequestration and biodiversity).
  • Develop innovative design methods that support and enhance ecological processes through data-driven optimization.

Required Experience
  • Proven experience developing and deploying geospatial machine learning models, deep generative models, or RL algorithms in practical research problems.
  • Ph.D. or equivalent experience in Computer Science, Machine Learning, Operations Research, or related fields.
  • Demonstrated experience working in cross-functional teams bridging ML research with ecology, architecture, or design.

Preferred Experience
  • Experience with GIS tools and remote sensing technologies for geospatial analysis.
  • Prolific corpus of digital or physical expressions rooted in process-driven research and design.
  • Industry experience combined with a background in leading research and producing striking work.

Technical Skills
  • Commitment to Nature-centric principles and a willingness to integrate technology and ecology.
  • Enthusiasm for pushing boundaries in design and science with innovative thinking.
  • Self-directed with an aptitude for nurturing collaborative teamwork across disciplines
Required Education/Certifications
  • Ph.D. in a relevant field (CS, ML, OR).

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