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Embedded Machine Learning Jobs in Florida (NOW HIRING)

Motorola

Embedded Software Engineer (DSP)

Plantation, FL · On-site

$63.80K - $97.60K/yr

Familiarity with Python is a plus, particularly for automation or in the context of AI/Machine Learning workflows. * Embedded Fundamentals: Experience with ARM-based or DSP microprocessor ...

Danfoss LLC

Sr. Embedded Engineer

Tallahassee, FL

$107.50K - $140.80K/yr

We promote from within and support your learning with mentoring, training, and access to global ... Information at a Glance Apply now Danfoss engineers solutions that increase machine productivity ...

Danfoss LLC

Sr. Embedded Software Specialist

Tallahassee, FL

$107.50K - $140.80K/yr

We promote from within and support your learning with mentoring, training, and access to global ... Information at a Glance Apply now Danfoss engineers solutions that increase machine productivity ...

Persona AI

Software Engineering Intern

Pensacola, FL · On-site

Machine learning applications in robotics and autonomous systems * Real-time software development and embedded systems programming * Collaborative software development in a fast-paced startup ...

Socure

$180K - $210K/yr

Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems. * Model Socure's embedded leadership competencies: continuous learning, effective ...

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$52.3K

$114.6K

$130K

How much do embedded machine learning jobs pay per year?

As of Jun 4, 2026, the average yearly pay for embedded machine learning in Florida is $114,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $129,300.00 per year, depending on experience, location, and employer.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

What are the key skills and qualifications needed to thrive in the Embedded Machine Learning position, and why are they important?

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.
More about Embedded Machine Learning jobs
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What job categories do people searching Embedded Machine Learning jobs in Florida look for? The top searched job categories for Embedded Machine Learning jobs in Florida are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Florida as of May 2026, with employment types broken down into 1% Locum Tenens, 4% Internship, 62% Full Time, 31% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $114,622 per year, or $55.1 per hour.

AI / Machine Learning Junior / Senior / Lead

Catalyst Labs, LLC

Miami, FL • On-site

Other

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

Job description

About the job AI / Machine Learning Junior / Senior / Lead
About Us
Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency thats deeply embedded in our clients recruitment operations.
We collaborate directly with Founders, CTOs, and Heads of AI at Tier 1 VC backed startups, scale ups and enterprise tech like Palatir, who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.This is a general / expression of interest, therefore by submitting your CV, you will be considered for upcoming roles with our clients.
Locations: Most of our client base is concentrated in California, New York and a few scattered across other States and Europe.
Who Can Apply: We are looking for professionals with demonstrated experience in AI, ML, and Data Science roles within reputed tech companies and/or from top 100 universities in the world. Visa sponsorship is available for existing H1b transfers. Student visas will only be considered on the academic pedigree - top 50 global universities.
Experience: From early-career engineers to senior ICs, leads and principals.
General Requirements by Role:

  • Proven experience building or deploying machine learning systems in production environments (not just academic or lab prototypes).
  • Background in a top technology company, Tier 1 VC backed startup, advanced research institute, or high-caliber engineering team.
  • Solid understanding of ML fundamentals, including model development, optimization, and evaluation.
  • Hands-on experience with at least one major area of specialization:
    • LLMs & Generative AI
    • Computer Vision
    • NLP / NLU
    • Reinforcement Learning
    • Recommendation Systems
    • Time Series & Forecasting
    • Applied Deep Learning
  • Familiarity with modern ML engineering workflows:
    • MLOps pipelines
    • Model monitoring & observability
    • Deployment to cloud or edge environments
    • Vector databases & embeddings
    • Retrieval-augmented pipelines
  • Experience with distributed systems, data infrastructure, or high-performance computing is a strong advantage.
  • Professionals with experience in AI Safety, alignment, privacy-preserving ML, or security-focused ML are also welcome.
  • Strong coding proficiency (Python preferred) and familiarity with relevant frameworks such as PyTorch, TensorFlow, JAX, LangChain, Ray, etc.
  • Experience mentoring engineers, leading technical initiatives, or driving cross-functional collaboration is valued.
  • Candidates with a track record of publications, open-source contributions, patents, or shipped products demonstrating real-world impact will stand out.
Why Work With Us?
  • Take advantage of the strong relationships we have built with Founders and CTOs.
  • Work with recruiters who understand the difference between a fine-tuned model and a foundation model and wont ask if you know Python.
  • We prioritize your confidentiality and privacy throughout the recruitment process.
  • No Spamming
  • Support refining your resume or portfolio specifically for the roles we shortlist you for.
  • Direct communication channels. Bypass gatekeepers and speak directly with the actual hiring manager and decision-makers.
  • Insight on compensation structures across geographies, including equity-heavy offers, research-focused roles, or hybrid IC/lead tracks.

Apply