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Embedded Machine Learning Engineer Jobs in Florida

Machine Learning Engineer - Generative Al Long term contract Sunrise, FL (Hybrid-3 days onsite) Direct client- Immediate client interview We are seeking a Machine Learning Engineer to design, build ...

Skills and Preferred Qualifications * 2+ years of experience in machine learning and software development. * Strong engineering skills, including Python, CUDA, C++. * Experience building distributed ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Sr. Machine Learning Engineer

Bradenton, FL · Remote

$111K - $146.40K/yr

Sr. Machine Learning Engineer The Sr. Machine Learning Engineer collaborates with the team of Data Scientists and Data Analysts in creating scalable, data-driven, customer-centric solutions, capable ...

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

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Embedded Machine Learning Engineer information

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

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 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 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 cities in Florida are hiring for Embedded Machine Learning Engineer jobs? Cities in Florida with the most Embedded Machine Learning Engineer job openings:
Infographic showing various Embedded Machine Learning Engineer job openings in Florida as of May 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Temporary. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Intraedge

Sunrise, FL • Hybrid

Other

Posted 5 days ago


Job description

Machine Learning Engineer - Generative Al

Long term contract

Sunrise, FL (Hybrid-3 days onsite)

Direct client- Immediate client interview

Job description:

We are seeking a Machine Learning Engineer to design, build, and deploy Generative Al solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAl use cases, from model selection to production-ready systems.

Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google Cloud Platform

Key Responsibilities

Develop and productionize GenAl 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.

Colaborate with product and platform teams to deliver scalable Al solutions.

Required Qualifications

Strong experience with LLMs (e.g., OpenAl, Anthropic, Llama, Mistral).

Hands-on experience with LangChain and/ or LangGraph.

Solid understanding of LLM memory architectures and state management.

Proficiency in Python and ML engineering best practices.

Nice to Have

Experience with Google Cloud Platform services (e.g.,Vertex Al, BigQuery, GCS).

Experience deploying ML/GenAl systems in production environments.


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About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

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