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Embedded Machine Learning Engineer Jobs in Florida

OptiTrack

Machine Learning & Operations Engineer

Miami, FL · Remote

$66.50K - $89.90K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

Lockheed Martin

AI/Machine Learning Engineer Senior

Orlando, FL · On-site +1

$114.30K - $150.70K/yr

... machine learning and feature engineering techniques
 • Deploying AI capabilities and tracking projects through to completion
 • Implementing best technical practices from the fields of ...

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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.

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What job categories do people searching Embedded Machine Learning Engineer jobs in Florida look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Florida are:
What cities in Florida are hiring for Embedded Machine Learning Engineer jobs? Cities in Florida with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
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.

Senior Specialist, AI / Machine Learning Data Engineer

BNY

Lake Mary, FL • On-site

$107.10K - $141.20K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Senior Specialist, AI / Machine Learning Engineer

We're seeking a future team member for the role of Senior Specialist, AI / Machine Learning Engineer to join our AI Hub team. This role is located in Lake Mary, FL.

This role is located in our AI Hub and is focused on building AI-powered tools and platforms that improve the way engineers design, build, test, and operate software. This is an exciting opportunity for a strong individual contributor who can apply AI and software engineering skills to develop practical solutions, contribute to technical innovation, and help deliver scalable capabilities in support of engineering teams.

In this role, you'll make an impact in the following ways:

  • Design, develop, and support applied AI solutions, contributing hands-on to machine learning and artificial intelligence products and features.
  • Bring solid knowledge of Applied AI, LLMs, prompt engineering, fine tuning, model evaluation, and approaches to building fit-for-purpose models and copilots for engineering use cases.
  • Perform technical research, experimentation, and prototyping to evaluate tools, frameworks, and model approaches, and help translate results into implementation recommendations.
  • Partner with engineers and stakeholders to understand requirements, workflows, and user needs, and contribute to success measures that demonstrate solution value and adoption.
  • Apply AI to improve the software development lifecycle and support builders, designers, and developers through reliable, secure, and effective tools and capabilities.
  • Contribute to the achievement of Application Development objectives by delivering high-quality engineering work, supporting team standards, and continuously building technical depth across AI and software engineering practices.

To be successful in this role, we're seeking the following:

  • Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required.
  • 2-6 years of experience in software development required; experience in the securities or financial services industry is a plus.
  • Advanced experience, preferably 5+ years, in applied AI/ML, software engineering, or model development, including experience building and testing production-oriented solutions.
  • Ability to work independently as a strong technical contributor while collaborating closely with peers and senior engineers on solution design and delivery.
  • Strong understanding of software engineering fundamentals, enterprise development practices, and modern AI/ML tooling, with an interest in scalable and sustainable architectures.
  • Ability to communicate technical concepts clearly, learn quickly, and work effectively with both technical and non-technical stakeholders.

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