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Remote Deep Learning Engineer Jobs in Kansas (NOW HIRING)

Overstory

Role & Team As a Staff Machine Learning Engineer at Overstory, you will lead the development and ... Strong background in deep learning, computer vision, or remote sensing * Skilled in designing end ...

PICTOR LABS INC

$89K - $123K/yr

The ideal candidate will have deep expertise in ML inference optimization, GPU programming, and ... Remote US Company: Pictor Labs Employment Type: Full-time Responsibilities * Design, development ...

Varsity Tutors

Machine Learning Tutor

Wichita, KS · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Varsity Tutors

Machine Learning Tutor

Overland Park, KS · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Nebius

Experience with deep learning frameworks (e.g., PyTorch, TensorFlow). * Familiarity with ML tools ... Remote Work Reimbursement: Up to $85/month for mobile and internet. * Disability & Life Insurance:

Harris

$70K - $100K/yr

A strong foundation in machine learning, deep learning, data engineering, and AI agent frameworks ... Remote work and more! About MACC: Telecommunication companies of all sizes across the United States ...

New

Harris

$70K - $100K/yr

A strong foundation in machine learning, deep learning, data engineering, and AI agent frameworks ... Remote work and more! About MACC: Telecommunication companies of all sizes across the United States ...

New

Wood Plc

Software Development Engineer

Topeka, KS · On-site +1

Experience with Machine Learning, Deep Learning, and/or AI * Experience with data processing ... remote sensing platforms * Understanding of IT protocols, networking, and database management

Ascend Learning

Senior Security Engineer

Leawood, KS · On-site +1

$111K - $152K/yr

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... Performs deep-dive investigations using endpoint telemetry, process execution data, and behavioral ...

Varsity Tutors

FE - Civil Engineering Tutor

Wichita, KS · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of FE Civil examination content covering mathematics, probability and statistics ...

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All JobsDeep Learning Engineer JobsRemote Deep Learning Engineer JobsRemote Deep Learning Engineer Jobs in Kansas

Remote Deep Learning Engineer information

See Kansas salary details

$9.8K

$74.8K

$124.9K

How much do remote deep learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote deep learning engineer in Kansas is $74,813.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,200.00 and $124,000.00 per year, depending on experience, location, and employer.

What is a remote deep learning engineer?

A Remote Deep Learning Engineer is a professional who works primarily online to design, develop, and implement deep learning models and algorithms. These engineers use neural networks and large datasets to solve complex problems in fields like computer vision, natural language processing, and more. Working remotely, they collaborate with team members via digital tools, write code, optimize models, and often deploy solutions to cloud environments. This role requires strong programming skills, experience with deep learning frameworks (like TensorFlow or PyTorch), and the ability to work independently in a distributed team setting.

What are the key skills and qualifications needed to thrive as a remote deep learning engineer?

To thrive as a Remote Deep Learning Engineer, you need a strong background in machine learning, deep learning frameworks, and programming languages like Python, usually supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (e.g., AWS, GCP), and version control systems is typically required, with certifications in AI or cloud technologies being advantageous. Excellent problem-solving, communication, and self-management skills make candidates stand out in remote environments. These skills and qualities are essential for developing effective AI solutions, collaborating across distributed teams, and driving innovation in the fast-evolving field of deep learning.

How do remote deep learning engineers typically collaborate with cross-functional teams despite working remotely?

Remote Deep Learning Engineers frequently collaborate with data scientists, product managers, and software engineers using digital tools such as Slack, Zoom, and collaborative code platforms like GitHub. Regular virtual meetings and sprint planning sessions help ensure alignment on project goals and milestones. Clear documentation and asynchronous communication are crucial for effective teamwork, especially when team members are in different time zones. This collaborative structure enables remote engineers to contribute meaningfully to model development, deployment, and integration while maintaining flexibility.

What is the difference between Remote Deep Learning Engineer vs Remote Machine Learning Engineer?

AspectRemote Deep Learning EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with deep learning frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch and development, model training, neural network designData analysis, model deployment, algorithm development
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce

Remote Deep Learning Engineers focus on designing and training neural networks for complex AI tasks, while Remote Machine Learning Engineers work on broader ML models and algorithms. Both roles require strong programming skills and knowledge of machine learning frameworks, but Deep Learning Engineers specialize in neural networks and large-scale data processing.

What are popular job titles related to Remote Deep Learning Engineer jobs in Kansas?

For Remote Deep Learning Engineer jobs in Kansas, the most frequently searched job titles are:

What job categories do people searching Remote Deep Learning Engineer jobs in Kansas look for?

The top searched job categories for Remote Deep Learning Engineer jobs in Kansas are:

What cities in Kansas are hiring for Remote Deep Learning Engineer jobs?

Cities in Kansas with the most Remote Deep Learning Engineer job openings:

Remote Deep Learning Engineer jobs near you

Staff Machine Learning Engineer - Wildfire

Overstory

On-site, Remote

Full-time

Re-posted 17 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