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Remote Embedded Machine Learning Jobs in Missouri

Jobgether

Join an innovative AI-focused environment where human expertise plays a key role in improving the accuracy and reliability of next-generation machine learning systems. In this freelance remote ...

Relativity

Principal Applied Scientist

Kansas City, MO · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Select the appropriate modeling approach for each problem, ranging from classical machine learning ...

Jobgether

Solid understanding of AI and machine learning concepts, including agent architectures, embeddings ... Fully remote work environment with flexibility across Europe, including the United Kingdom.

GRVTY

Imagery Scientist (EO) - Senior

Saint Louis, MO · On-site +1

$89K - $121K/yr

Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies ... Experience applying CV and machine learning (ML) techniques to EO imagery and data to address ...

Healthcare Fraud Shield

Data Scientist

Chesterfield, MO · On-site +1

Utilize advanced mathematical models, machine learning algorithms, operations research techniques ... Remote work eligible REMOTE WORK REQUIREMENTS: * Must have high speed Internet (satellite is not ...

Jobgether

$80K - $110K/yr

The position is ideal for individuals who enjoy solving complex machine learning problems while ... Fully remote work flexibility across Europe, with optional hybrid office access in select locations ...

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

Remote Embedded Machine Learning information

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

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 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 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 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 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
Associate Game Developer (Cocos2d) - Remote

Associate Game Developer (Cocos2d) - Remote

micro1 AI

Kansas City, MO • Remote

$50 - $110/hr

Part-time

Posted 8 days ago

Job description

Job Title: Cocos2d-x Junior Game Developer


Job Type: Contractor


Location: Remote


Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Develop and refine game logic, mechanics, and features using Cocos2d-x for prototype and production-level projects.
  2. Collaborate closely with the customer's team to provide high-quality real-world input for AI training processes.
  3. Create, modify, and troubleshoot game assets and scenes to support a diverse set of training objectives.
  4. Test, debug, and optimize Cocos2d-x code to ensure robust and efficient gameplay experiences.
  5. Document code and processes thoroughly, ensuring clarity for both technical and non-technical stakeholders.
  6. Engage in open, clear written and verbal communication to report project status and challenges.
  7. Work iteratively in response to feedback, consistently improving deliverables for AI development needs.


Required Skills and Qualifications:

  1. Solid knowledge of Cocos2d-x and hands-on experience with 2D game development workflows.
  2. Strong problem solving and troubleshooting abilities in a game development context.
  3. Experience collaborating remotely with distributed teams in a fast-paced environment.
  4. Excellent written and verbal communication skills, with a focus on clear, concise updates and documentation.
  5. Ability to follow technical specifications and adapt to evolving project requirements.
  6. Understanding of game design principles and player experience optimization.
  7. Self-motivated, detail-oriented, and eager to grow within a dynamic AI training environment.


Preferred Qualifications:

  1. Experience working on projects for AI training or data generation purposes.
  2. Familiarity with additional game engines or programming languages.
  3. Background in collaborating with AI or machine learning specialists.

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