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Remote Embedded Machine Learning Jobs in Missouri

Jobgether

$70 - $100/hr

The project offers a flexible, remote environment where specialized machine learning expertise can directly influence the quality of AI systems. As a freelance contributor, you will work ...

New

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 ...

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 MLOps principles, and a proven track record in client-facing implementation. The successful candidate ...

Jobgether

Fully remote work from India. * Opportunity to work on large-scale machine learning models and high-performance inference systems. * Exposure to advanced model optimization, systems engineering, and ...

Third-Party Job Posts

Location - Remote (Europe) How You'll Make an Impact: As a Staff Machine Learning Engineer , you will play a key role in building and implementing features that empower lodging customers to make data ...

Jobgether

You will contribute to features spanning data preparation, machine learning, visualization, MLOps ... Remote working opportunity within the United Kingdom. * Strong focus on innovation, engineering ...

Bunge North America

Data Scientist

Chesterfield, MO · On-site +1

Translate complex business problems into data-driven analytics and machine learning tasks, then ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

Bunge

Data Scientist

Chesterfield, MO · On-site +1

Translate complex business problems into data-driven analytics and machine learning tasks, then ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

Jobgether

You will work at the intersection of machine learning research and systems engineering to develop ... Remote working arrangement with the flexibility to contribute from locations worldwide. * Direct ...

Jobgether

$97K - $132K/yr

The position combines statistical modeling, machine learning, generative AI, and agent-based ... Fully remote work environment with a standard 40-hour work week . * Limited travel, generally less ...

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Showing results 21-40

All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Missouri

Remote Embedded Machine Learning information

What is a remote embedded machine learning engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

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

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.

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

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

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

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

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

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

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

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

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

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

Remote Embedded Machine Learning jobs near you

Machine Learning (ML) AI Task Auditor - Freelance AI Trainer Project

Remote

Jobgether
See more jobs at Jobgetherexternal

$70 - $100/hr

Contractor

Medical, PTO

Posted 3 days ago

New

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 Machine Learning (ML) AI Task Auditor - Freelance AI Trainer Project based in Netherlands.

This freelance opportunity is designed for experienced Machine Learning professionals who want to apply their technical expertise to the development and evaluation of advanced AI systems.
You will audit machine learning tasks used to train and evaluate AI models, ensuring they are technically accurate, realistic, reproducible, and practical.
The role involves reviewing model development workflows, data preprocessing pipelines, algorithms, and testing approaches against rigorous technical standards.
You will identify data pipeline flaws, model training inefficiencies, algorithmic logic errors, and other issues that could affect task quality.
Your feedback will help improve the reliability and technical integrity of AI training and evaluation workflows.
The project offers a flexible, remote environment where specialized machine learning expertise can directly influence the quality of AI systems.
As a freelance contributor, you will work independently on challenging technical assignments while helping ensure AI evaluation tasks reflect real-world machine learning practices.

Accountabilities
  • Evaluate machine learning tasks to determine whether they are technically accurate, realistic, solvable, reproducible, and supported by reliable tests and evaluation criteria.
  • Review model development workflows, data preprocessing pipelines, and machine learning implementations for technical correctness and practical relevance.
  • Assess whether algorithms, training approaches, and expected outcomes are logically sound and appropriately defined.
  • Identify data pipeline flaws, model training inefficiencies, algorithmic logic errors, and other technical issues that may compromise task quality.
  • Rigorously test and troubleshoot complex machine learning scenarios to validate task behavior and expected results.
  • Provide clear, actionable technical feedback on identified issues and recommend improvements where appropriate.
  • Apply specialized machine learning knowledge to ensure AI training and evaluation tasks meet high standards of accuracy, rigor, and reproducibility.
  • Document technical findings clearly and consistently across assigned project tasks.
Requirements
  • Demonstrable professional experience and deep technical knowledge in Machine Learning, including model development and data preprocessing pipelines.
  • Strong hands-on experience with machine learning frameworks such as PyTorch or TensorFlow.
  • Strong understanding of machine learning algorithms, model training workflows, data preparation, and technical evaluation practices.
  • Strong analytical and problem-solving skills, with the ability to rigorously test, troubleshoot, and evaluate complex technical scenarios.
  • Excellent attention to detail and the ability to identify subtle data, model, algorithmic, testing, and reproducibility issues.
  • Ability to objectively assess technical tasks against requirements for accuracy, realism, solvability, and reliable evaluation.
  • Strong written communication skills for providing precise, constructive, and actionable technical feedback.
  • Ability to work independently and apply specialized expertise within a freelance, project-based environment.
  • Candidates will be considered for one area of specialization based on their professional experience; expertise across other domains is not required.
  • Ability to provide a secure computer and reliable high-speed internet connection for freelance project work.
Benefits
  • Compensation of $70-$100 per hour, with the exact rate determined based on experience, expertise, and geographic location.
  • Final compensation may vary from the published range following evaluation of your qualifications and location.
  • Freelance contract structure offering flexibility for project-based work.
  • Remote work environment.
  • Opportunity to contribute directly to the training and evaluation of advanced AI systems.
  • Opportunity to apply specialized Machine Learning expertise to technically challenging AI evaluation projects.
  • Health insurance, paid time off, and other company-sponsored employee benefits are not provided under the freelance contract.
  • Contractors are responsible for supplying their own secure computer and high-speed internet connection.
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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