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Online Machine Learning Jobs in Missouri (NOW HIRING)

Jobgether

$94K - $124K/yr

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights. This role sits at the ...

Jobgether

$11.50 - $15.50/hr

Machine Learning Data Associate based in Netherlands. This is an opportunity to lead engaging, high ... online environment. You will also contribute to curriculum refinement and continuous course ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code editing, RAG, etc. Our team of Machine Learning Engineers have high impact by advancing the current ...

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Online Machine Learning information

What is online machine learning?

Online machine learning is a method where models are trained incrementally as new data becomes available, rather than being trained all at once on a fixed dataset. This approach is particularly useful in environments where data arrives continuously, such as real-time analytics, recommendation systems, and fraud detection. Online learning algorithms update their knowledge with each new data point, allowing them to adapt quickly to changes and trends. This makes them ideal for applications that require immediate responses and adaptability to evolving data streams.

What are the key skills and qualifications needed to thrive as an online machine learning engineer?

To excel as an Online Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning algorithms, often supported by a relevant degree and experience with streaming data. Familiarity with tools such as Apache Kafka, Spark Streaming, Python, TensorFlow, and real-time data processing frameworks is critical. Problem-solving ability, adaptability, and effective communication are essential soft skills for collaborating with multidisciplinary teams and responding to rapidly changing data. These competencies are crucial for building scalable, responsive models that provide timely insights in dynamic production environments.

How does collaboration typically work between online machine learning engineers and data scientists in a project setting?

Online machine learning engineers often work closely with data scientists to ensure that the models they develop can be effectively deployed and updated in real-time environments. While data scientists may focus on feature engineering, model selection, and initial training using historical data, online machine learning engineers are responsible for integrating these models into production systems and implementing mechanisms for continuous learning from live data streams. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth collaboration and ensure that the models remain accurate and efficient as new data arrives.

What is the difference between Online Machine Learning vs Data Scientist?

AspectOnline Machine LearningData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related fields; certifications in ML or data analysisBachelor's or master's in CS, statistics, or related fields; advanced degrees often preferred
Work EnvironmentTech companies, startups, research labs; focus on real-time data processingCorporate, consulting, or research settings; focus on data analysis and modeling
Industry UsageMachine learning applications, AI development, real-time systemsData analysis, predictive modeling, business insights

Online Machine Learning specialists focus on developing algorithms that learn continuously from streaming data, often in real-time environments. Data Scientists analyze large datasets to extract insights, build models, and support decision-making. While both roles require knowledge of machine learning, Online Machine Learning emphasizes real-time data processing, whereas Data Scientists focus on data analysis and modeling for strategic insights.

What are the most commonly searched types of Machine Learning jobs in Missouri?

The most popular types of Machine Learning jobs in Missouri are:

What cities in Missouri are hiring for Online Machine Learning jobs?

Cities in Missouri with the most Online Machine Learning job openings:

Online Machine Learning jobs near you

Senior Geospatial Machine Learning Engineer

Jobgether

On-site, Remote

$94K - $124K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Geospatial Machine Learning Engineer based in Netherlands.

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights.
This role sits at the intersection of machine learning, geospatial technology, and climate innovation, helping solve complex challenges impacting critical infrastructure.
You will work on building and improving algorithms that analyze vegetation, assess risks, and support smarter decision-making for energy systems.
The position offers the opportunity to own impactful projects from experimentation through production while collaborating with multidisciplinary engineering and scientific teams.
You will contribute to the evolution of data-driven products using cutting-edge ML techniques, remote sensing data, and geospatial technologies.
This is an ideal opportunity for an experienced engineer passionate about applying AI to create meaningful environmental impact.

Accountabilities:

The Senior Geospatial Machine Learning Engineer will design, develop, and improve machine learning solutions that leverage geospatial data to deliver innovative environmental intelligence products. This role requires strong technical ownership, collaboration, and the ability to translate complex data challenges into practical solutions.

  • Develop new geospatial intelligence products using Python-based geospatial libraries, machine learning, and deep learning techniques.
  • Improve existing solutions through data exploration, model optimization, debugging, and performance enhancements.
  • Work with satellite and aerial imagery, raster and vector datasets, and geospatial workflows to solve real-world challenges.
  • Lead technical projects from planning and experimentation through implementation, delivery, and stakeholder communication.
  • Build tools and processes to evaluate model performance, product impact, and data-driven prioritization.
  • Collaborate with data engineering, product, platform, and delivery teams throughout the full machine learning product lifecycle.
  • Contribute to technical direction, engineering practices, and team culture within a fast-growing environment.
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Requirements:

The ideal candidate is an experienced machine learning or geospatial engineer with strong expertise in Python, scientific computing, and applied AI. They should be comfortable working independently, leading projects, and applying advanced technology to environmental and infrastructure challenges.

  • 8-10+ years of experience in machine learning engineering, geospatial engineering, remote sensing, or a closely related technical field.
  • Strong Python programming skills with hands-on experience using geospatial libraries such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas.
  • Experience with scientific Python tools including NumPy, SciPy, scikit-learn, and Pandas.
  • Practical experience developing deep learning solutions using frameworks such as PyTorch and/or TensorFlow.
  • Strong understanding of satellite imagery, aerial imagery, and geospatial raster/vector data processing.
  • Experience with workflow orchestration tools such as Dagster or similar platforms.
  • Ability to independently lead initiatives, manage technical projects, and communicate results effectively.
  • Passion for climate technology and using machine learning to address complex environmental problems.

Nice-to-have qualifications:

  • Experience with vegetation science, forestry, energy infrastructure, or utility-related technologies.
  • Familiarity with observability tools such as Sentry and Grafana.
  • Previous experience in climate tech, geospatial AI, remote sensing, or environmental data companies.
Benefits:
  • Fully remote work environment with flexibility across eligible locations.
  • Opportunity to work on impactful climate technology projects using AI and satellite data.
  • Ability to influence technical direction, processes, and product development within a growing organization.
  • Collaboration with a diverse international team across engineering, product, design, and platform functions.
  • Exposure to cutting-edge machine learning, geospatial technologies, and real-world applications.
  • Inclusive culture focused on solving meaningful problems through technology.
  • Opportunity for professional growth in a mission-driven environment.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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