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Remote Embedded Machine Learning Jobs in Florida

Celsius

Director, Business Transformation

Boca Raton, FL · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... products, analytics, machine-learning solutions, and AI agents that teams actually use ... Partner with embedded Transformation Leads in Sales, Commercial, Marketing, Operations, Finance ...

IBR (Imagine Believe Realize)

Senior Azure Data Architect

Rockledge, FL · On-site +1

$58.75 - $78.50/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Key Skills: * Expertise in statistical modeling, machine learning algorithms, and data mining ... Hybrid and Remote work opportunities to support work-life balance Salary Range: $135,000.00 - $165 ...

Lee Health

Cloud Engineer - Azure

Fort Myers, FL · On-site +1

$78K - $101K/yr

Remote - Florida Department: IS Information Technology Svcs Work Type: Full Time Shift: Shift 1/8 ... Masters degree in Computer Science, Machine Learning, or related discipline preferred. Experience ...

Lee Health

Cloud Engineer - Azure

Fort Myers, FL · On-site +1

$78K - $101K/yr

Remote - Florida Department: IS Information Technology Svcs Work Type: Full Time Shift: Shift 1/8 ... Master's degree in Computer Science, Machine Learning, or related discipline preferred. Experience ...

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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 Florida?

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

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

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

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

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

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

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

Remote Embedded Machine Learning jobs near you

ML Engineer - AI Coding Expert - AI Trainer

Mercor

Miami, FL • Remote

$85/hr

Full-time

Posted 5 hours ago

Posted today

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: ML Engineer (Coding Agent Experience)
Type: Contract
Compensation: $85/hour
Location: Remote

Role Responsibilities

  • Use frontier AI coding agents to complete and evaluate complex machine learning and AI engineering tasks.
  • Review model-generated implementations involving model training, inference systems, MLOps, and LLM applications.
  • Identify bugs, edge cases, performance issues, and failure modes.
  • Compare outputs from multiple frontier models and assess their strengths and weaknesses.
  • Apply professional engineering judgment to realistic ML engineering scenarios.

Qualifications

Must-Have

  • 2+ years of professional machine learning engineering experience.
  • Experience building production ML systems, model deployment infrastructure, LLM applications, or AI-powered products.
  • Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
  • Ability to evaluate model-generated machine learning implementations and technical tradeoffs.

Preferred

  • Experience deploying ML systems to production.

Compensation & Legal

  • $400 per accepted task.
  • Compensation is tied to accepted work.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.


#hiringmercor