1

Machine Learning Geospatial Jobs in Oregon (NOW HIRING)

Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications. * Possess the knowledge and capability to develop advanced machine learning models and ...

Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications. * Possess the knowledge and capability to develop advanced machine learning models and ...

Data Scientist

OR · On-site +1

... in machine learning and predictive modeling. * Proposed personnel possess the knowledge and ... Knowledge of data visualization, feature selection, and geospatial analytics is required.

... in machine learning and predictive modeling. * Proposed personnel possess the knowledge and ... Knowledge of data visualization, feature selection, and geospatial analytics is required.

Senior / Staff Software Engineer, Mapping

OR · On-site +1

$141K - $242K/yr

... geospatial systems, spatial databases, and tooling such as QGIS, GDAL, or PostGIS. - Familiarity with Machine Learning pipelines or integrating AI models into production engineering systems ...

... construction, geospatial, government, transportation, and more. AECO: Trimble is empowering ... Our impact is tangible, from connected machines that save fuel to data-driven insights that reduce ...

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 are popular job titles related to Machine Learning Geospatial jobs in Oregon?

For Machine Learning Geospatial jobs in Oregon, the most frequently searched job titles are:

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

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

Infographic showing various Machine Learning Geospatial job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Machine Learning Engineer, Operations Research

Instacart

OR • On-site, Remote

$204K/yr

Full-time

Re-posted 13 days ago


Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

28th of 64 rated delivery companies


Job description

Overview:

We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space - including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale.

The Logistics & ML group is responsible for the intelligence and execution behind Instacart's fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

About the Job:

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.


About You:

Minimum Qualifications:

  • 3+ years of industry experience using machine learning to solve real-world problems with large datasets
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels
  • Graduate degree (masters or PhD) in Operations Research or Industrial Engineering or closely related field

Preferred Qualifications:

  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems


#LI-Remote


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012