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Hourly Embedded Machine Learning Jobs in Florida

Deloitte

Cyber - SecOps - Consultant

Tallahassee, FL

... machine learning to address cyber-specific challenges. Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a ...

Deloitte

Cyber - SecOps - Consultant

Miami, FL · On-site

... machine learning to address cyber-specific challenges. Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a ...

Deloitte

Cyber - SecOps - Consultant

Tampa, FL

... machine learning to address cyber-specific challenges. Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a ...

Deloitte

Cyber - SecOps - Consultant

Jacksonville, FL · On-site

... machine learning to address cyber-specific challenges. Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a ...

Pae

AI Modeling Specialist (Senior)

Doral, FL · On-site

Design, develop, and deploy machine learning, artificial intelligence, and advanced statistical ... hourly rate listed for this position is provided as a good-faith estimate of what the company ...

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All JobsHourly Embedded Machine Learning JobsHourly Embedded Machine Learning Jobs in Florida

Hourly Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as an hourly embedded machine learning engineer, and why are they important?

To thrive as an Hourly 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 engineering or a related field. Familiarity with tools such as TensorFlow Lite, embedded Linux, microcontroller development environments, and model optimization frameworks is typically required. Strong problem-solving skills, adaptability, and effective communication help you address complex technical challenges and collaborate with cross-functional teams. These skills are crucial for designing efficient, real-time ML solutions that operate reliably on resource-constrained embedded devices.

How does an hourly embedded machine learning professional typically collaborate with hardware and software teams during a project?

As an Hourly Embedded Machine Learning professional, you will often work closely with both hardware and software engineering teams to ensure that machine learning models are efficiently integrated into embedded systems. This typically involves frequent communication to align on hardware constraints, such as memory and processing power, and to optimize algorithms for real-time performance. You may also participate in joint debugging sessions and code reviews to address integration issues and streamline deployment. Collaboration is key, as successful projects depend on the seamless interaction between machine learning solutions and the embedded hardware platform.

What is an hourly embedded machine learning engineer?

An Hourly Embedded Machine Learning engineer is a professional who specializes in developing and deploying machine learning models on embedded systems, such as microcontrollers, IoT devices, or edge devices, and is compensated on an hourly basis rather than a salaried or project-based arrangement. These engineers work to optimize algorithms so they can run efficiently on devices with limited computing power, memory, and energy resources. Their responsibilities often include model selection, quantization, optimization, and integration of machine learning pipelines into hardware. Hiring on an hourly basis allows for flexibility in project scope and duration, making it ideal for companies with specific, time-limited needs. They often collaborate with hardware engineers, data scientists, and software developers to create intelligent embedded solutions.

What is the difference between Hourly Embedded Machine Learning vs Hourly Data Scientist?

AspectHourly Embedded Machine LearningHourly Data Scientist
CredentialsKnowledge of embedded systems, programming, ML algorithmsDegree in Data Science, Statistics, or related field
Work EnvironmentEmbedded hardware, IoT devices, real-time systemsData analysis, modeling, visualization in office or cloud
Industry UsageConsumer electronics, automotive, IoT devicesFinance, healthcare, marketing, research

Hourly Embedded Machine Learning specialists focus on integrating ML models into embedded systems and hardware, often working with IoT devices and real-time constraints. In contrast, Hourly Data Scientists analyze large datasets to develop predictive models primarily in cloud or office environments. While both roles require programming skills, embedded ML emphasizes hardware integration, whereas data science centers on data analysis and visualization.

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 Hourly Embedded Machine Learning jobs in Florida? For Hourly Embedded Machine Learning jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Hourly Embedded Machine Learning jobs in Florida look for? The top searched job categories for Hourly Embedded Machine Learning jobs in Florida are:
What cities in Florida are hiring for Hourly Embedded Machine Learning jobs? Cities in Florida with the most Hourly Embedded Machine Learning job openings:
Hourly Embedded Machine Learning jobs near you
Infographic showing various Hourly Embedded Machine Learning job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Python / Machine Learning Engineer - Ft Lauderdale

FormativGroup

Fort Lauderdale, FL • On-site, Remote

$45 - $50/hr

Full-time

Re-posted 10 days ago

Job description

Summary

The role of the Senior Python Engineer is to design, develop, and deploy machine learning solutions that transform data into actionable insights, while ensuring scalability, performance, and integration into production systems. This role focuses on building and operationalizing machine learning models, supporting end-to-end data workflows, and integrating AI capabilities into broader application ecosystems. The individual will work closely with engineering and data teams to deliver reliable, production-ready solutions.

Key Responsibilities

  • Develop and maintain machine learning models using Python, leveraging techniques such as regression, classification, clustering, and ensemble methods
  • Design and deploy scalable AI/ML solutions utilizing deep learning frameworks (e.g., TensorFlow, PyTorch, Keras)
  • Perform data preparation activities including cleansing, transformation, and feature engineering to support model accuracy
  • Evaluate model performance and iterate to improve reliability and predictive outcomes
  • Build and integrate RESTful APIs (e.g., Flask, FastAPI) to enable model consumption within applications
  • Collaborate with cross-functional teams to embed ML solutions into production environments

Required Qualifications

  • 6-8 + years of experience in Python-based development roles and AI/ML
  • Strong proficiency in Python and core data science libraries such as NumPy, Pandas, and Scikit-learn
  • Hands-on experience implementing machine learning and deep learning models in real-world applications
  • Solid understanding of data engineering concepts, including preprocessing, feature engineering, and model evaluation techniques
  • Experience working with SQL or NoSQL databases
  • Familiarity with version control systems (e.g., Git) and collaborative development practices

Additional / Preferred Skills

  • Experience deploying models into production environments
  • Familiarity with scalable ML pipelines and MLOps concepts
  • Exposure to cloud-based AI/ML services (AWS, Azure, GCP)

Location

  • This role is a Hybrid role that requires candidate to go onsite 3 days in office/2 days remote. Candidates are preferred in Fort Lauderdale, FL. Candidates must reside within the physical US.
  • Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa currently.
  • To be considered for this position, candidates must reside in one of the following U.S. states: FL.
  • Candidates residing outside these states are not eligible for consideration currently.
  • Not open to 3rd party/C2C engagement

We are committed to pay equity and transparency. The compensation range for this position represents our good faith estimate of the range we reasonably expect to pay for this role at the time of posting. The actual compensation offered will be determined based on factors such as the candidate's experience, skills, education, work location, and internal equity.

In addition to hourly pay, employees may be eligible for discretionary bonuses, commissions, or other incentive programs, as well as a comprehensive benefits package that includes medical, dental, vision, 401(k), paid time off, etc.

Estimated hourly Compensation Range:
$45—$50 USD

FormativGroup operates within the critical middle layer of business technology, where applications and systems connect infrastructure to business processes. We are specialists who help the middle market take full advantage of their technology investments with deep, industry-centric expertise, all in one place, to unify fragmented systems. With deep technical expertise across cloud architecture, system integration, AI, and data strategy, we bridge the gap between business goals and modern platforms.

FormativGroup is an equal opportunity employer providing opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

ADA Specifications: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of this position.

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