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Remote Embedded Machine Learning Jobs in Taylor, MI

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QA Engineer - AI Trainer

Detroit, MI · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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QA Engineer - AI Trainer

Dearborn, MI · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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SDLC Engineer - AI Trainer

Ann Arbor, MI · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

DataAnnotation

SDLC Engineer - AI Trainer

Detroit, MI · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

DataAnnotation

QA Engineer - AI Trainer

Warren, MI · Remote

$50 - $100/hr

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

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All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Taylor, MI

Remote Embedded Machine Learning information

See Taylor, MI salary details

$65K

$142.4K

$161.5K

How much do remote embedded machine learning jobs pay per year?

As of Jul 11, 2026, the average yearly pay for remote embedded machine learning in Taylor, MI is $142,390.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,100.00 and $160,600.00 per year, depending on experience, location, and employer.

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.
Remote Embedded Machine Learning jobs near you
DevOps Engineer Live Streaming- Wixom, MI

DevOps Engineer Live Streaming- Wixom, MI

J&B Medical

Wixom, MI • On-site, Remote

$80K - $110K/yr

Full-time

Re-posted 12 days ago

Job description

Job Type
Full-time
Description
J&B Virtual Solutions - we provide Telehealth Solutions.
J&B Virtual Solutions is a telehealth software solutions company that offers a complete system for health care professionals. VideoDoc® is our HIPAA and HITECH compliant telehealth platform that offers extensive video engagement options and utilizes our patented remote patient monitoring technology to capture, secure, and retrieve information on patient physiologies.
A DevOps Engineer plays a critical role in bridging the gap between software development and IT operations. They are responsible for designing and managing automated systems for software deployment, testing, and infrastructure provisioning. Working closely with developers, system administrators, and other teams, they aim to enhance the software development lifecycle. DevOps Engineers utilize tools like Kubernetes, Docker, and cloud platforms (AWS, Azure, GCP) to manage infrastructure and environments, ensuring high availability and scalability of applications
*******THIS POSITION IS FULL TIME IN OUR WIXOM MICHIGAN OFFICE. NO REMOTE, NO RELOCATION ALLOWANCE & NO SPONSORSHIP - now or in the future**********
Essential Functions:
  • Collaborate with the team to implement well-architected and cost-effective cloud solutions in Azure.
  • Design, build, and maintain both AWS and Azure-based networks, virtual machines, and Site Recovery solutions.
  • Automate & Optimize infrastructure deployment and maintenance using Infrastructure-as-Code (IaC) tools like Terraform, CloudFormation, and Ansible.
  • Manage & Scale production and non-production environments with AWS EC2, S3, RDS, Lambda, and Azure VMs.
  • Monitor & Troubleshoot system performance, ensuring high availability using Azure Monitor and Insights and AWS CloudWatch.
  • Enhance Security by building and maintaining security controls, compliance protocols, and best practices for protecting customer data.
  • Manage and secure network infrastructure using FortiGate firewalls, ensuring optimal security, VPN connectivity, and traffic management across cloud and on-prem environments.
  • Support Developers by refining CI/CD pipelines, managing deployments, and improving automation strategies.
  • Perform Backup & Recovery Operations and resolve complex technical issues in Azure and hybrid cloud environments.
  • Document & Innovate-Refactor pipelines, write documentation, and stay ahead of the latest cloud technologies.

Key Competencies:
  • 4-5+ years of hands-on experience in a DevOps role or cloud infrastructure management.
  • Deep AWS expertise, including EC2, S3, RDS, DynamoDB, Lambda, Cognito, Step Functions, Athena, etc.
  • Azure Cloud proficiency, particularly in Azure Virtual Machines, Site Recovery, and on-prem to Azure migrations.
  • Strong scripting & automation skills-Bash, Python, PowerShell, or equivalent.
  • Proficiency with Git and CI/CD tools (Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps Pipelines).
  • Experience with FortiGate firewalls for network security, VPN management, traffic filtering, and intrusion prevention.
  • Infrastructure as Code (IaC) experience with Terraform, CloudFormation, or Ansible.
  • Monitoring & Logging expertise using Azure Monitor & AWS CloudWatch.
  • Experience troubleshooting production environments and improving system reliability.
  • Strong teamwork & communication skills-you enjoy working with developers to streamline workflows.

Position Type:
This is a full-time onsite in Wixom position; 40-hour minimum, with the expectation to maintain a regular work schedule. Occasional evening and weekend work may be required as job duties demand.
Must be authorized to work in U.S. is a precondition of employment.
Requirements
Required Education and Experience:
  • Bachelor's Degree or equivalent experience.
  • At least 5 years of experience in an IT environment.

Preferred Experience/SKILLS:
  • Machine Learning on AWS (SageMaker, AI Services, etc.).
  • AWS Redshift for data warehousing.
  • Video streaming protocols (HLS, WebRTC, RTP, MPEG-DASH, Smooth Streaming).
  • Open-source video software (FFMPEG, x264).
  • DLNA/UPnP

THIS POSITION IS FULL TIME IN OUR WIXOM MICHIGAN OFFICE. NO REMOTE, NO RELOCATION ALLOWANCE & NO SPONSORSHIP (now or in the future)
Salary Description
$80000.00 to $110,000.00

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