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Machine Learning Geospatial Jobs in Seattle, WA (NOW HIRING)

... machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial AI, geospatial analytics, and generative AI solutions. This role sits at the intersection of ...

... machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial AI, geospatial analytics, and generative AI solutions. This role sits at the intersection of ...

... machine learning systems across Weyerhaeuser's AI portfolio, including pricing optimization, industrial AI, geospatial analytics, and generative AI solutions. This role sits at the intersection of ...

You will bridge the gap between Geospatial Intelligence and Machine Learning to revolutionize our path planning and scheduling algorithms. Your primary north star? Increasing deliveries per hour (DPH ...

Software Engineer II

Redmond, WA · On-site

$133K - $219K/yr

Applies engineering techniques and machine learning solutions to solve complex geospatial suggestion and location search problems in production. * Works on core technology and engineering stack to ...

Spanning traditional machine learning, generative AI, and agentic AI, this role ensures solutions ... Awareness of geospatial data and AI applications (e.g., LiDAR, satellite imagery, and ESRI ...

Spanning traditional machine learning, generative AI, and agentic AI, this role ensures solutions ... Awareness of geospatial data and AI applications (e.g., LiDAR, satellite imagery, and ESRI ...

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Machine Learning Geospatial information

See Seattle, WA salary details

$21

$33

$53

How much do machine learning geospatial jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for machine learning geospatial in Seattle, WA is $33.17, according to ZipRecruiter salary data. Most workers in this role earn between $25.72 and $38.56 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 job categories do people searching Machine Learning Geospatial jobs in Seattle, WA look for?

The top searched job categories for Machine Learning Geospatial jobs in Seattle, WA are:

Infographic showing various Machine Learning Geospatial job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $68,995 per year, or $33.2 per hour.

Senior Machine Learning Engineer (Active Secret Clearance)

Striveworks

Tacoma, WA • On-site

$185K - $230K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 days ago


Job description

"In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it." - Dr. Jim Rebesco, Cofounder and CEO, Striveworks 

The government's demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.

Striveworks was built to solve that problem.

What you'll build

Since 2018, we have delivered the most trusted AI systems operating in real-world use cases-providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.

As a Senior Machine Learning Engineer, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working directly with customers, data scientists, software engineers, and DevOps engineers, you'll define requirements and orchestrate complex data engineering pipelines. You'll also develop machine learning models and custom analytics applied to image, video, text, geospatial, time series, and structured data.. Your work will inform the future of Chariot, our proprietary AI operations platform. The work extends to the field, with mission-critical deployments, direct customer contact, and insights that shape what we build next.

What it's like here

We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership-because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.

What we're looking for
  • A BS degree in computer science, machine learning, or a related discipline and 6+ years of relevant experience
  • Demonstrated experience delivering data-centric systems
  • Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of TensorFlow, PyTorch, and/or scikit-learn
  • Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language
  • Proficiency with modern software engineering tools and processes
  • Active Secret (or above) US security clearance and US citizenship

The following isn't required, but we'd love to see it:

  • An advanced degree in data science, machine learning, computer science, or a related discipline
  • Knowledge of relevant architectures and design patterns for client-server systems
  • Experience implementing and deploying software into containerized or cloud environments
  • Experience with a variety of unstructured data types
  • Experience building AI agents, agentic workflows, or agentic systems
  • Experience defining, scoping, planning, and delivering complex, production-level technical solutions
  • Experience leading, managing, or mentoring small, cross-functional engineering teams 
  • Experience delivering technology solutions in secure government environments

You will be hybrid/on site at customer locations at Joint Base Lewis-McChord in Tacoma, WA. You will be expected to travel up to 25% of the time.

Compensation

The anticipated base pay range for this position is $185,000-$230,000/year. Striveworks' total compensation package includes a competitive base salary, equity grants, and cash bonuses.

Benefits include:
  • Medical/dental/vision insurance
  • Voluntary life, long-term disability, accident, and hospital indemnity insurance
  • HSA and FSA (including dependent care FSA) plans
  • 401(k) plan
  • Unlimited PTO
  • Paid parental leave

Ready to build systems that work for a mission that matters? Let's talk.

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact People Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.