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Hourly Remote Machine Learning Engineer Jobs in Kansas

Our data products - derived from satellite imagery and machine learning - give utilities a clearer ... Experience with remote sensing, satellite imagery, or other earth observation data * SQL or ...

Senior Security Engineer

Leawood, KS · On-site +1

$111.40K - $152.70K/yr

... remote workers in cities across the U.S., Ascend Learning was recognized by Newsweek and Plant-A ... WHAT YOU'LL DO The Senior Security Engineer will contribute to achievement of P&L objectives for ...

$158K - $269K/yr

To learn more visit: www.waabi.ai As a Research Engineer in Calibration, you will create the next ... machine learning, or self-driving technology. The US yearly salary range for this role is: $158,000 ...

We are looking for a Full Stack Engineer to join our team to train AI models. You will measure the ... are paid hourly up to $60 USD/hour, with bonuses for high-quality and high-volume work ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

Wichita, KS · Remote

$40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Benefits This is a full-time or part‐time REMOTE position You'll be able to choose which projects ... hourly starting at $40+ USD per hour, with bonuses on high‐quality and high‐volume work ...

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Hourly Remote Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as an Hourly Remote Machine Learning Engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What does an Hourly Remote Machine Learning Engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.
What are popular job titles related to Hourly Remote Machine Learning Engineer jobs in Kansas? For Hourly Remote Machine Learning Engineer jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Hourly Remote Machine Learning Engineer jobs in Kansas look for? The top searched job categories for Hourly Remote Machine Learning Engineer jobs in Kansas are:
What cities in Kansas are hiring for Hourly Remote Machine Learning Engineer jobs? Cities in Kansas with the most Hourly Remote Machine Learning Engineer job openings:

Other

Posted 13 days ago


Job description

Role & Team

As a Solutions Engineer at Overstory, you'll turn our vegetation intelligence into operational impact for utility customers. Our data products - derived from satellite imagery and machine learning - give utilities a clearer picture of where vegetation poses risk to their power lines. Vegetation-caused outages are a leading cause of power disruption and a growing driver of wildfire risk, and climate change is making the problem harder. You'll deliver analyses with technical and geospatial depth, build tools and workflows that make our work scale, and help customers actually act on what we provide. You'll use geospatial analysis, Python, and Overstory's data products to solve real utility problems today, and help shape what becomes a scalable product capability tomorrow.

This role is a great fit for someone who loves working with large geospatial datasets and wants to grow into customer advisory, product, or operational work at a high-growth mission-driven company. Highlights:

  • Ownership: Innovate on, deliver, and grow a critical capability for a fast-growing business - from customer delivery through scalable productization.
  • Impact: Make a tangible, scalable contribution to climate resilience in the power sector.
  • Skills: Use your geospatial and technical toolkit while building product judgment, customer-facing depth, startup operating experience, and your craft with AI tools.
  • Trajectory: Grow your career at a high-growth company, staying in Solutions Engineering or with pathways into Product, Customer Success, Sales, or Strategy.

Time Zone Requirement: North America (EST preferred)

What You'll Do

On a typical day, you might be: running satellite imagery through a pipeline and validating the output; debugging a geospatial join in Python; reviewing a draft analysis with a Customer Success Manager before it goes to a customer; talking with a utility vegetation manager to walk through findings and adjust based on what you hear; refactoring a notebook into a reusable script for the team; or sketching out how a recurring customer ask could become a product feature.

Ensure our customers get the most possible value out of Overstory through technical and analytical work
  • Own customer projects end-to-end, from data requests and processing through analysis to customer-ready outputs, in close partnership with Customer Success.
  • Work with large geospatial datasets (vector and raster) from Overstory's platform, customers, and third-party sources - process, validate, analyze, and turn them into outputs customers can act on.
  • Build rapport with customer counterparts. Translate technical findings into recommendations that change decisions and lead to better outcomes for our customers.
Build the technical foundations for what we productize next
  • Identify patterns across customer work that are worth standardizing and productizing. Convert one-off projects into repeatable artifacts.
  • Strengthen engineering quality so analytical work is easier to validate, hand off, and scale.
  • Partner with product and engineering to build the productization roadmap.
  • Strengthen the analytics workflows and infrastructure that support both customer impact and future productization.
Skills & Experience
  • Passionate about tackling climate challenges with data-driven solutions.
  • 2-4 years of professional experience working with large, complex geospatial datasets in a customer- or stakeholder-facing capacity.
  • Proficiency with a Python-driven analytical and engineering stack - Python, Jupyter, git/GitHub, and command-line workflows.
  • Experience successfully managing multiple projects simultaneously.
  • Demonstrated attention to detail and care with data.
  • Demonstrable experience (or at a minimum a serious interest in) leveraging AI tooling to amplify your work.
  • Proven ability to solve ambiguous problems and collaborate effectively with stakeholders.
  • Excellent communication, including translating technical findings for non-technical audiences and building rapport with customer counterparts.
Nice To Have
  • Background in utility operations, infrastructure, or vegetation management
  • Experience with remote sensing, satellite imagery, or other earth observation data
  • SQL or experience with data engineering pipelines
  • Prior work in a high-growth startup or mission-driven company