{"schemaVersion":"jobsearcher.job.v1","id":"1f21aa6d9a2271b09bcf84c8","url":"https://jobsearcher.com/jobs/1f21aa6d9a2271b09bcf84c8","canonicalUrl":"https://jobsearcher.com/jobs/1f21aa6d9a2271b09bcf84c8","title":"Spatial Machine Learning Engineer","description":"Spatial Machine Learning Engineer | RemoteRole OverviewThe Spatial Machine Learning Engineer transforms customer spatial data into deployable indoor-intelligence solutions. This role blends GIS, indoor mapping, data engineering, and machine learning to deliver high-quality spatial analytics and model outputs.Roles & ResponsibilitiesCustomer Onboarding & Spatial DeploymentOwn and execute technical portions of customer onboarding.Prepare customer sites, accounts, locations, buildings, floors, and platform resources.Configure indoor maps and floor plans for platform use.Troubleshoot deployment and configuration issues.Develop repeatable onboarding processes and documentation.Machine Learning & Data EngineeringPrepare customer datasets for ML model training.Run training, validation, and evaluation workflows.Use MLflow or similar tools for experiment tracking and model management.Evaluate model performance and identify data quality or coverage issues.Apply proper training/validation/testing methodologies.Perform exploratory data analysis to identify relationships, anomalies, bias, and data quality problems.Work with large spatial, sensor, and wireless datasets.Use Python to automate data preparation, analysis, validation, and operational workflows.GIS & Indoor MappingWork with GIS datasets, coordinate systems, spatial transformations, and geospatial tooling.Prepare and georeference indoor floor plans.Validate spatial accuracy between floor plans, collected data, and coordinate systems.Work with vector and raster geospatial data.Assist with extracting, transforming, and maintaining indoor spatial data.Wireless / Wi-Fi (Preferred)Understanding of Wi-Fi operation (2.4, 5, 6 GHz).Knowledge of channels, channel widths, RSSI, and RF propagation.Awareness of indoor signal behavior and measurement variability.Required QualificationsGIS or geospatial data experience.Experience with indoor maps, floor plans, or spatial datasets.Georeferencing and coordinate transformation experience.Strong Python programming skills.Experience with Git and modern development workflows.SQL and relational database experience.Experience training and evaluating machine learning models.Understanding of ML fundamentals (train/val/test splits, leakage, overfitting, sampling).Experience with AWS or another major cloud platform.Comfortable working in Linux environments.Preferred QualificationsExperience with MLflow or similar experiment-management platforms.Rust programming experience.Infrastructure-as-code experience (Pulumi preferred).Docker, containers, or Kubernetes experience.Familiarity with AWS services (S3, EC2, RDS, EKS, CloudWatch, IAM, VPC).Background in statistics, mathematics, engineering, or computer science.Understanding of statistical concepts (correlation, covariance, sampling, distributions, outliers, bias, significance).Experience with large datasets or automated ML/data pipelines.","company":"Alis Software","rawCompany":"alis software","city":"Denver","state":"CO","isRemote":false,"isActive":false,"createdAt":"2026-10-15T13:03:44.109Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.02","title":"Geographic Information Systems Technologists and Technicians","slug":"geographic-information-systems-technologists-and-technicians"},{"code":"19-2099.01","title":"Remote Sensing Scientists and Technologists","slug":"remote-sensing-scientists-and-technologists"}],"industries":[{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541360","title":"Geophysical Surveying and Mapping Services","slug":"geophysical-surveying-and-mapping-services"},{"code":"541370","title":"Surveying and Mapping (except Geophysical) Services","slug":"surveying-and-mapping-except-geophysical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Spatial Machine Learning Engineer","description":"Spatial Machine Learning Engineer | RemoteRole OverviewThe Spatial Machine Learning Engineer transforms customer spatial data into deployable indoor-intelligence solutions. This role blends GIS, indoor mapping, data engineering, and machine learning to deliver high-quality spatial analytics and model outputs.Roles & ResponsibilitiesCustomer Onboarding & Spatial DeploymentOwn and execute technical portions of customer onboarding.Prepare customer sites, accounts, locations, buildings, floors, and platform resources.Configure indoor maps and floor plans for platform use.Troubleshoot deployment and configuration issues.Develop repeatable onboarding processes and documentation.Machine Learning & Data EngineeringPrepare customer datasets for ML model training.Run training, validation, and evaluation workflows.Use MLflow or similar tools for experiment tracking and model management.Evaluate model performance and identify data quality or coverage issues.Apply proper training/validation/testing methodologies.Perform exploratory data analysis to identify relationships, anomalies, bias, and data quality problems.Work with large spatial, sensor, and wireless datasets.Use Python to automate data preparation, analysis, validation, and operational workflows.GIS & Indoor MappingWork with GIS datasets, coordinate systems, spatial transformations, and geospatial tooling.Prepare and georeference indoor floor plans.Validate spatial accuracy between floor plans, collected data, and coordinate systems.Work with vector and raster geospatial data.Assist with extracting, transforming, and maintaining indoor spatial data.Wireless / Wi-Fi (Preferred)Understanding of Wi-Fi operation (2.4, 5, 6 GHz).Knowledge of channels, channel widths, RSSI, and RF propagation.Awareness of indoor signal behavior and measurement variability.Required QualificationsGIS or geospatial data experience.Experience with indoor maps, floor plans, or spatial datasets.Georeferencing and coordinate transformation experience.Strong Python programming skills.Experience with Git and modern development workflows.SQL and relational database experience.Experience training and evaluating machine learning models.Understanding of ML fundamentals (train/val/test splits, leakage, overfitting, sampling).Experience with AWS or another major cloud platform.Comfortable working in Linux environments.Preferred QualificationsExperience with MLflow or similar experiment-management platforms.Rust programming experience.Infrastructure-as-code experience (Pulumi preferred).Docker, containers, or Kubernetes experience.Familiarity with AWS services (S3, EC2, RDS, EKS, CloudWatch, IAM, VPC).Background in statistics, mathematics, engineering, or computer science.Understanding of statistical concepts (correlation, covariance, sampling, distributions, outliers, bias, significance).Experience with large datasets or automated ML/data pipelines.","datePosted":"2026-10-15T13:03:44.109Z","dateModified":"2026-10-15T13:03:44.109Z","hiringOrganization":{"@type":"Organization","name":"Alis Software","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Denver","addressRegion":"CO","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"1f21aa6d9a2271b09bcf84c8"},"url":"https://jobsearcher.com/jobs/1f21aa6d9a2271b09bcf84c8"}}