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Remote Machine Learning Architect Jobs in Missouri

Jobgether

$80K - $110K/yr

Join a fully remote, mission-driven climate technology environment where machine learning and ... architecture, model evaluation, and product delivery. Your work will directly contribute to ...

Jobgether

Fully remote working model. * Opportunity to work with modern LLM, RAG, machine learning, and AI platform technologies. * Significant technical ownership and influence over enterprise AI architecture ...

Catawiki

The Data Team, which covers the full data spectrum of Machine Learning, Analysis and Data ... Where you'll be This role is based in Amsterdam but we can offer remote work from the following ...

Jobgether

$49 - $67.25/hr

Knowledge of GPU clusters and techniques for optimizing machine learning workloads. * Working ... Remote working flexibility and significant ownership over your work. * Career growth and continuous ...

Koantek

Senior AI Engineer

Chesterfield, MO · Remote

$54.75 - $70.50/hr

This remote role requires a blend of advanced Machine Learning (ML) expertise, deep knowledge of ... architect role, focused on technical implementation and delivery. Excellent verbal and written ...

Jobgether

$79K - $104K/yr

The role spans managed AWS machine learning services, open-source ML tooling, model serving ... This is a fully remote independent contractor opportunity within a globally distributed team, with ...

Third-Party Job Posts

Location - Remote (Europe) How You'll Make an Impact: As a Staff Machine Learning Engineer , you ... Architectural Expertise: Proven track record in designing, deploying, and maintaining production ...

Third-Party Job Posts

Remote (Europe) How You'll Make an Impact: As a Staff Software Engineer in Revenue Intelligence ... processing, machine-learning workflows, and production infrastructure. We value pragmatic ...

Jobgether

This is a fully remote opportunity for an independent researcher who wants their work to move ... Design, develop, train, and evaluate machine learning models capable of interpreting complete CT ...

Kohl's

$95K - $131K/yr

Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance ...

Jobgether

$42.75 - $55/hr

Familiarity with GPU-based infrastructure, accelerated computing, machine learning and AI workloads ... Remote work flexibility from Europe, with a high degree of ownership over how you work. * Career ...

Perficient

Data Architect - Azure and Big Data

Saint Louis, MO · On-site +1

$61.75 - $80.50/hr

Provide architectural assessments, strategies, and roadmaps for one or more technologies including ... Machine Learning Studio, HDInsight, Polybase, Azure Data Lake Analytics, Azure Data Warehouse ...

Jobgether

$159K - $215K/yr

This is a high-impact engineering leadership role at the intersection of machine learning, data ... Fully remote work environment with a globally distributed team. * Opportunity to lead a ...

Jobgether

$44 - $58.50/hr

Experience supporting production data platforms and machine learning systems. * Practical MLOps ... Fully remote position within European time zones. * Opportunity to work on infrastructure ...

Jobgether

$100K - $120K/yr

Competitive annual salary of $100,000-$120,000 . * Full-time opportunity with a remote working model . * Opportunity to work on cutting-edge AI, machine learning, and GenAI solutions. * Hands-on ...

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Remote Machine Learning Architect information

What is a remote machine learning architect?

A Remote Machine Learning Architect is a professional who designs, builds, and oversees machine learning systems and infrastructure while working remotely. They collaborate with data scientists, engineers, and stakeholders to define system architecture, select appropriate algorithms, and ensure scalable deployment of machine learning models. Their responsibilities include setting technical standards, optimizing workflows, and ensuring integration with existing IT infrastructure, all accomplished through remote communication and collaboration tools. This role requires strong expertise in machine learning, cloud platforms, and software engineering.

How does a remote machine learning architect typically collaborate with distributed teams to deliver successful projects?

As a Remote Machine Learning Architect, effective collaboration with globally distributed teams is essential. You will often coordinate with data scientists, software engineers, and business stakeholders via virtual meetings, shared documentation, and project management tools. Regular communication, clear documentation of model designs, and version control practices are crucial to ensure alignment and smooth integration of machine learning solutions. Adopting agile methodologies and being proactive in addressing time zone differences help maintain project momentum and foster a productive team environment.

What are the key skills and qualifications needed to thrive as a remote machine learning architect, and why are they important?

To thrive as a Remote Machine Learning Architect, you need deep expertise in machine learning algorithms, model development, and a solid background in computer science or related fields, often supported by an advanced degree. Familiarity with cloud platforms (such as AWS, Azure, or GCP), deep learning frameworks (like TensorFlow or PyTorch), and relevant certifications are typically expected. Strong problem-solving, communication, and project management skills help you collaborate effectively with distributed teams and stakeholders. These skills and qualities are crucial for designing scalable ML solutions that drive business value in a remote work environment.

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

AspectRemote Machine Learning ArchitectData Scientist
Required CredentialsMaster's or PhD in CS, AI, or related fields; certifications in ML frameworksMaster's in Data Science, Statistics, or related; certifications in data analysis tools
Work EnvironmentDesigning ML systems, collaborating with engineering teams, remote or on-siteAnalyzing data, building models, often remote or in-office
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Remote Machine Learning Architects focus on designing and implementing scalable ML systems, while Data Scientists analyze data and build models. Both roles require advanced degrees and often overlap in skills, but their core responsibilities differ in scope and focus.

What are popular job titles related to Remote Machine Learning Architect jobs in Missouri?

For Remote Machine Learning Architect jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Architect jobs in Missouri look for?

The top searched job categories for Remote Machine Learning Architect jobs in Missouri are:

What cities in Missouri are hiring for Remote Machine Learning Architect jobs?

Cities in Missouri with the most Remote Machine Learning Architect job openings:

Remote Machine Learning Architect jobs near you
Infographic showing various Remote Machine Learning Architect job openings in Missouri as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% Remote job distribution.

Senior Geospatial Machine Learning Engineer

Jobgether

On-site, Remote

$80K - $110K/yr

Full-time

Posted 21 days ago

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.

Join a fully remote, mission-driven climate technology environment where machine learning and satellite imagery are used to address critical infrastructure challenges.
As part of the Vegetation Modeling team, you will build advanced ML solutions that identify vegetation-related risks before they contribute to wildfires or power outages.
You will work with large-scale geospatial datasets, satellite and aerial imagery, computer vision, and deep learning to create production-ready intelligence products.
The role combines hands-on engineering with technical ownership, giving you the opportunity to lead projects from initial planning through delivery.
You will collaborate with teams across Europe and the Americas, influencing data pipelines, platform architecture, model evaluation, and product delivery.
Your work will directly contribute to improving grid resilience while applying technology to complex environmental and climate challenges.
This is an opportunity for a senior ML professional who wants meaningful technical challenges and measurable real-world impact.

Accountabilities
  • Develop and deploy new vegetation intelligence products using machine learning, deep learning, computer vision, geospatial Python libraries, and large-scale satellite or aerial imagery.
  • Explore geospatial datasets, identify opportunities for model improvement, optimize existing ML solutions, and troubleshoot production issues.
  • Maintain and enhance existing vegetation modeling products to improve accuracy, reliability, scalability, and overall impact.
  • Lead technical projects end-to-end, from defining objectives and planning implementation through execution, delivery, and evaluation.
  • Develop measurement frameworks, evaluation tooling, and performance metrics that enable data-driven decisions about model quality and impact.
  • Monitor production models and investigate performance issues using appropriate observability, monitoring, and debugging tools.
  • Work closely with upstream data ingestion teams to influence data pipelines, processing workflows, and platform architecture.
  • Partner with downstream product and delivery teams to ensure geospatial ML outputs can be effectively integrated into customer-facing solutions.
  • Use tools such as QGIS, Dagster, Sentry, Grafana, or equivalent platforms to analyze data, manage workflows, monitor systems, and diagnose issues.
  • Communicate technical findings, project progress, model performance, and business impact clearly to technical and non-technical stakeholders.
  • Contribute to engineering and ML best practices across a distributed team working across Europe and the Americas.
  • Help translate complex environmental and geospatial problems into scalable machine learning solutions that support climate resilience and critical infrastructure.
Requirements:
  • 5+ years of professional experience as a Machine Learning Engineer, Data Scientist, or in a closely related role, with demonstrated experience building and deploying production machine learning or deep learning models.
  • Proven experience developing computer vision or deep learning models using satellite or aerial imagery.
  • Strong proficiency in Python and geospatial Python libraries such as rasterio, geopandas, shapely, GDAL, or equivalent technologies.
  • Solid understanding of geospatial data structures, formats, processing workflows, and analysis techniques.
  • Professional experience with ML and deep learning frameworks such as PyTorch, TensorFlow, scikit-learn, or comparable tools.
  • Experience designing, implementing, or maintaining data pipelines using orchestration and workflow tools such as Dagster, Airflow, dbt, or equivalent systems.
  • Experience with QGIS or comparable geospatial visualization and analysis software.
  • Strong understanding of model evaluation, performance measurement, monitoring, and debugging in production environments.
  • Ability to work effectively with large-scale, complex datasets and translate technical findings into practical product or business decisions.
  • Strong project ownership skills, with the ability to independently drive initiatives from planning through execution and delivery.
  • Excellent communication and collaboration skills, particularly in distributed and cross-functional environments.
  • Experience with multispectral or hyperspectral satellite imagery is a strong advantage.
  • Background in vegetation analysis, forestry, agriculture, environmental monitoring, or related geospatial applications is highly valued.
  • Familiarity with observability and monitoring tools such as Grafana, Sentry, Prometheus, or similar platforms is a plus.
  • A genuine interest in climate technology, environmental applications, and using advanced technology to solve complex real-world problems is highly desirable.
  • Candidates should be comfortable working in a fully remote environment and collaborating across multiple time zones.
Benefits:
  • Fully remote working environment.
  • Opportunity to work on technology with direct applications in climate action, wildfire prevention, and electrical grid resilience.
  • Meaningful ownership of machine learning products and the opportunity to lead projects from concept through production.
  • Collaboration with a geographically distributed team spanning Europe and the Americas.
  • Exposure to advanced satellite imagery, geospatial data, computer vision, and large-scale machine learning systems.
  • High-impact technical challenges involving real-world environmental and infrastructure problems.
  • Competitive senior-level compensation package expected, commensurate with experience.
  • Opportunity to contribute to the development of production ML systems rather than purely experimental or research-focused models.
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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