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Embedded Machine Learning Engineer Jobs in Miami, FL

Machine Learning Engineer

Sunrise, FL ยท On-site

$90K - $110K/yr

Role - Machine Learning Engineer Experience Required -8+ Years We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs)

Machine Learning Engineer

Miami, FL ยท On-site

$80 - $120/hr

Preferred Qualifications PhD in Mathematics, Engineering, Physics or related field; 4-8 years experience working in Machine Learning; Experience with deep learning frameworks like TensorFlow or ...

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Embedded Software Engineer

Miramar, FL ยท On-site

$110K - $135K/yr

Key Responsibilities Computer Vision & Machine Learning * Develop, train, and deploy object ... Embedded & Systems Integration * Deploy inference to edge compute on production equipment; optimize ...

Machine Learning Engineer

Fort Lauderdale, FL ยท On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Machine Learning Engineer

Miami, FL ยท On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

About Opendoor At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It ...

Machine Learning Engineer

Miami, FL ยท On-site

$150 - $230/hr

About the Role -- Senior and Above You're interviewing for Opendoor's ML team which seeks to automate and refine every decision made in our product. We don't slot into silos; you'll build where you ...

Machine Learning Engineer II

Coral Gables, FL ยท On-site

$92K - $126K/yr

Job Summary The Machine Learning Engineer II supports the discovery, design, and delivery of AI- and automation-enabled solutions that improve operational workflows. The role partners with business ...

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Embedded Machine Learning Engineer information

See Miami, FL salary details

$67K

$146.7K

$166.4K

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

As of Aug 25, 2026, the average yearly pay for embedded machine learning engineer in Miami, FL is $146,703.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,800.00 and $165,500.00 per year, depending on experience, location, and employer.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

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

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Miami, FL?

For Embedded Machine Learning Engineer jobs in Miami, FL, the most frequently searched job titles are:

What cities near Miami, FL are hiring for Embedded Machine Learning Engineer jobs?

Cities near Miami, FL with the most Embedded Machine Learning Engineer job openings:

Machine Learning Engineer

Sunrise, FL โ€ข On-site

$90K - $110K/yr

Full-time

Re-posted 3 days ago


Job description

Job Description
Role -  Machine Learning Engineer
Experience Required -8+ Years
 
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
 
Must Have Technical/Functional Skills:
 
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
• Implement short-term and long-term memory strategies for LLM-based systems.
• Optimize prompts, retrieval pipelines, and orchestration logic.
• Collaborate with product and platform teams to deliver scalable AI solutions.
Required Qualifications 
• Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral)
• Hands-on experience with LangChain and/or LangGraph.
• Solid understanding of LLM memory architecture and state management.
• Proficiency in Python and ML engineering best practices.
Nice to Have
• Experience with GCP services (e.g., Vertex AI, BigQuery, GCS).
• Experience deploying ML/GenAI systems in production environments.
• data scientist
• Can do ML model
 
Roles & Responsibilities
 
• Design, develop, and deploy GenAI applications using LLMs.
• Build and implement agentic workflows using LangChain/LangGraph.
• Develop ML models and production-ready AI solutions.
• Implement and manage LLM memory and state management strategies.
• Optimize prompts, retrieval pipelines, and orchestration workflows.
• Collaborate with product and platform teams to deliver scalable AI solutions.
• Deploy, monitor, and maintain AI/ML systems in production environments.
• Evaluate and integrate open-source and proprietary LLMs.
 
Base Salary Range : $90,000 to $110,000 Per Annum