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Remote Edge Ai Machine Learning Jobs in Kansas (NOW HIRING)

Overstory

... by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain ... Strong background in deep learning, computer vision, or remote sensing * Skilled in designing end ...

Varsity Tutors

Machine Learning Tutor

Overland Park, KS · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Varsity Tutors

Machine Learning Tutor

Wichita, KS · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

PICTOR LABS INC

$89K - $123K/yr

This role offers the opportunity to work at the intersection of cutting-edge AI and life-saving healthcare technology, making a tangible impact on patient outcomes. Location: Remote US Company:

StackAdapt

StackAdapt is a remote-first company, and we are open to candidates located anywhere in the US or ... Lead the creation and optimization of advanced machine learning algorithms-from developing new ...

Finite State

Design and optimize API contracts, edge endpoints, and event flows using Next.js (server components ... Continuous Learning: Stay ahead of trends in AI-assisted engineering, agentic systems, application ...

Rockwell Automation

$54.50 - $74.75/hr

This is remote based role with location either in the US or Ontario, Canada. Primary ... AI, and machine learning initiatives. The Essentials : You will Have: * Bachelor's degree in ...

Finite State

Design and optimize API contracts, edge endpoints, and event flows using Next.js (server components ... Continuous Learning: Stay ahead of trends in AI-assisted engineering, agentic systems, application ...

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Remote Edge Ai Machine Learning information

What is the difference between Remote Edge Ai Machine Learning vs Data Scientist?

AspectRemote Edge Ai Machine LearningData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with ML frameworksBachelor's or Master's in Statistics, CS, or related fields; strong analytical skills
Work EnvironmentRemote, often on edge devices or IoT systemsTypically office or remote, analyzing data in cloud or on-premises
Industry UsageAI development, IoT, autonomous systemsBusiness analytics, research, product development

Remote Edge Ai Machine Learning specialists focus on deploying ML models on edge devices, often requiring knowledge of embedded systems. Data Scientists analyze large datasets to extract insights, usually working in cloud environments. While both roles require strong ML fundamentals, their work environments and application areas differ significantly.

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Remote Edge Ai Machine Learning jobs near you

Staff Machine Learning Engineer - Wildfire

Overstory

On-site, Remote

Other

Posted 20 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 
  • 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