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Remote Embedded Machine Learning Jobs in Texas (NOW HIRING)

Senior Software Engineer - Remote

Austin, TX ยท Remote

$121K - $160K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Senior Software Engineer - Remote

Texas City, TX ยท Remote

$104K - $138K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

... remote within a mutually acceptable location. #LI-Hybrid Success Looks Like: * AI systems move ... Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

AI Lead Engineer

Dallas, TX ยท On-site +1

$101K - $133K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills * Artificial Intelligence (AI) & Machine Learning (ML) * Deep Learning * Generative AI (GenAI) * Large Language Models (LLMs) * Prompt ...

AI Lead Engineer

Dallas, TX ยท On-site +1

$101K - $133K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills Artificial Intelligence (AI) & Machine Learning (ML) Deep Learning Generative AI (GenAI) Large Language Models (LLMs) Prompt ...

... Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline Must have * Understanding of various machine learning algorithms (e.g. SVM, Random Forests ...

Showing results 41-60

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 Texas?

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

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

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

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

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

Senior Software Engineer - Remote

YO AI Labs

Austin, TX โ€ข Remote

$121K - $160K/yr

Full-time

Posted 26 days ago


Job description

Job Title: Senior Software Engineer

Job Type: Contract

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.

We are seeking strong Software Engineers to join our customer's team with expertise in Python3, Java, Rust, Go, C++, or TypeScript. This is a unique opportunity to directly impact the next generation of AI by leveraging your advanced engineering skills in a dynamic, remote setting.

Required Skills and Qualifications:

  • Proficiency in Python3, Java, Rust, or TypeScript, with additional experience in C++ or Go considered a strong asset.
  • Deep understanding of algorithms, data structures, and performance tuning.
  • Demonstrated experience in debugging complex software issues and delivering maintainable solutions.
  • Strong background in feature development and codebase refactoring.
  • Proven ability to optimize software for performance and scalability.
  • Exceptional written and verbal communication skills, with a keen attention to detail.
  • Track record of success in collaborative, cross-functional teams, ideally in remote settings.


Preferred Qualifications:

  • Previous experience working on large-scale, distributed codebases.
  • Familiarity with modern AI or machine learning systems is a plus, though not required.
  • Background in participating in rigorous code reviews and contributing to the development of software best practices.