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Remote Monitoring Evaluation Learning Jobs in Kansas

Overstory

Partner with wildfire science and product teams to define modeling objectives and evaluation ... Collaborate with MLOps peers to streamline training, inference, and monitoring in production ...

Ascend Learning

Psychometrician

Leawood, KS · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Headquartered in Burlington, MA, with additional office locations and hybrid and remote workers in ... Design and conduct efficacy evaluations of learning products and assessments * Design and conduct ...

Ascend Learning

Manager User Experience

Leawood, KS · On-site +1

$113K/yr

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  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... evaluations that support each designer's development and career growth. * Set clear expectations ...

Ascend Learning

Sr Manager FP&A

Leawood, KS · On-site +1

$106K - $144K/yr

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  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... Maintain dashboards to monitor capitalization rates, project spend, and early warning indicators.

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Remote Monitoring Evaluation Learning information

What is the difference between Remote Monitoring Evaluation Learning vs Remote Data Analyst?

AspectRemote Monitoring Evaluation LearningRemote Data Analyst
Primary FocusMonitoring, evaluating, and learning from programs or projects to improve outcomesAnalyzing data sets to identify trends, generate reports, and support decision-making
Required SkillsMonitoring tools, evaluation methodologies, learning frameworks, data collectionStatistical analysis, data visualization, database management, programming skills
Work EnvironmentFieldwork, program sites, remote collaboration with teamsOffice or remote, primarily computer-based work
Common CertificationsMonitoring and Evaluation (M&E) certifications, learning frameworksData analysis certifications, statistical software training

Remote Monitoring Evaluation Learning professionals focus on assessing program performance and fostering continuous improvement through evaluation and learning. In contrast, Remote Data Analysts primarily analyze data to support strategic decisions. While both roles require data skills, M&E emphasizes evaluation methodologies and learning frameworks, whereas Data Analysts focus on statistical analysis and data management.

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Remote Monitoring Evaluation Learning jobs near you

Staff Machine Learning Engineer - Wildfire

Overstory

On-site, Remote

Full-time

Re-posted 14 days ago

Job description

Role & Team

As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation structure, fuel loads, and wildfire risk from satellite and environmental data. You'll help shape the next generation of Overstory's modeling capabilities by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain expertise.

Reporting to our VP of Product Engineering, you'll work closely with data scientists, ML engineers, and product teams to ensure our wildfire models are accurate, robust, and production-ready - balancing scientific rigor with practical engineering excellence. As a senior technical leader, you'll mentor other engineers, drive architectural decisions, and define standards for modeling, experimentation, and deployment across Overstory.

Time zone requirement: Eastern North America (NST, AST, EST)

What You'll Do

In collaboration with data, ML, and science colleagues, you will:

  • Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies.
  • Design and maintain robust data and feature pipelines for large-scale geospatial and temporal data.
  • Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to real-world impact.
  • Build reproducible experimentation frameworks and model evaluation workflows.
  • Scale models from research to production with a focus on performance, reliability, and explainability.
  • Lead the evolution of ML systems, tooling, and processes - ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable.
  • Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments.
Skills & Experience
  • Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by the opportunity to reduce wildfire risk through data-driven insights
  • 10+ years of experience designing and building production-grade ML pipelines and systems 
  • You have a background in wildfire science, forestry, or remote sensing
  • Strong background in deep learning, computer vision, or remote sensing
  • Skilled in designing end-to-end ML systems - from data ingestion and preprocessing to deployment and monitoring
  • Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, Spark, or GeoPandas
  • Familiarity with GCP and Vertex AI, or similar cloud-based ML platforms
  • Strong communication skills and ability to collaborate across technical and scientific domains
  • Comfortable leading architectural discussions and mentoring other engineers
Nice To Have
  • Background in wildfire science, forestry, or remote sensing
  • Experience integrating physics-based models with ML or working with active learning and uncertainty quantification
  • Experience in model interpretability and data provenance for environmental ML systems
  • Experience with deep learning models for weather or climate data
  • Experience in remote-first or globally distributed teams

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer
  • Competitive, location-specific compensation and benefits 
  • Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
  • Home office stipend, coworking and ongoing education budgets 
  • A company culture that genuinely embodies each of our core values
  • To be part of truly mission-driven work that reduces wildfires, protects earth's natural resources and helps solve our climate crisis

Apply