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Machine Learning Jobs in Florida (NOW HIRING)

The Data Scientist, Machine Learning will support Basketball Operations by developing and deploying machine learning models to inform decision making across player evaluation, game strategy, and ...

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Machine Learning information

See Florida salary details

$19.1K

$31.8K

$65.8K

How much do machine learning jobs pay per year?

As of May 30, 2026, the average yearly pay for machine learning in Florida is $31,822.00, according to ZipRecruiter salary data. Most workers in this role earn between $24,300.00 and $34,400.00 per year, depending on experience, location, and employer.

What is a Machine Learning job?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

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

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

What are some typical day-to-day responsibilities in a Machine Learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.
What are the most commonly searched types of Machine Learning jobs in Florida? The most popular types of Machine Learning jobs in Florida are:
What cities in Florida are hiring for Machine Learning jobs? Cities in Florida with the most Machine Learning job openings:
Infographic showing various Machine Learning job openings in Florida as of May 2026, with employment types broken down into 50% Full Time, 48% Part Time, 1% Contract, and 1% Nights. Highlights an 97% Physical, 2% Hybrid, and 1% Remote job distribution, with an average salary of $31,822 per year, or $15.3 per hour.
Machine Learning Engineer

Full-time

Posted 21 days ago


Roper Technologies rating

8.2

Company rating: 8.2 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

74th of 183 rated software companies


Job description

Roper Technologies is seeking a Machine Learning Engineer to help design, build, and deploy advanced AI systems across our portfolio of market-leading software businesses. 
This role will focus on developing scalable machine learning products and services, shared AI components, and intelligent agents that drive meaningful business impact. Depending on experience level, the role may involve leading architectural initiatives, mentoring engineers, and shaping technical strategy. 
 
We are looking for hands-on engineers who are excited about building production-grade AI systems—not just prototypes—and who thrive in a high-impact, applied environment. Candidates who have demonstrated ability to think through product as well as engineering are highly desired.
 
What You’ll Do 
 
AI & ML System Development 
  • Design, build, and deploy machine learning models and AI systems in production environments 
  • Develop components such as:
    • Model inference services 
    • Data and feature pipelines
    • Complex recommendation and matching services
    • Vision based analysis systems
    • Evaluation and monitoring pipelines 
  • Optimize models for performance, reliability, and cost efficiency      
Intelligent Agents & Applied AI 
  • Contribute to the development of AI agents and multi-step workflow automation systems 
  • Build systems that integrate with enterprise tools and APIs 
  • Implement tool-use frameworks, memory mechanisms, and evaluation loops 
  • Experiment with LLMs, foundation models, and fine-tuning approaches 
  • Help translate AI research advances into practical, scalable solutions 
Engineering Excellence 
  • Write high-quality, maintainable, and well-tested code 
  • Participate in architecture design and technical reviews 
  • Contribute to CI/CD pipelines and MLOps workflows 
  • Implement observability and monitoring for AI systems in production 
  • Follow security, compliance, and responsible AI best practices 
Cross-Functional Collaboration 
  • Partner with product, data engineering, and infrastructure teams 
  • Help identify high-impact AI use cases within portfolio companies 
  • Support integration of shared AI components into business applications 
  • Communicate technical tradeoffs clearly to both technical and non-technical stakeholders 
Qualifications 
 
We welcome candidates across a range of experience levels. The scope and seniority of responsibilities will scale accordingly.  
Required 
  • 3+ years of experience in software engineering, data science, or machine learning (more for senior roles) 
  • Experience building and deploying production software systems 
  • Strong programming skills in Python (experience in additional languages is a plus) 
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) 
  • Understanding of modern AI architectures, including LLM-based systems 
  • Experience working with cloud environments (AWS, Azure, or GCP) 
  • Strong problem-solving skills and attention to detail 
 
Preferred  
  • Experience with:
    • Fine tuning, experimentation, etc.
    • Rapid development using AI tools 
    • Agent frameworks and orchestration tools 
    • Distributed systems or microservices architecture 
    • Model monitoring and evaluation frameworks 
  • Experience building reusable libraries or shared infrastructure 
  • Exposure to SaaS products or enterprise software environments 
  • Background in optimizing models for performance and cost
Leveling & Growth 
 
We are hiring across multiple experience levels: 
  • Intermediate ML Engineer – Contributes independently to projects, builds production features, collaborates cross-functionally. 
  • Senior ML Engineer – Owns complex systems end-to-end, drives architectural decisions, mentors others. 
  • Principal / Staff ML Engineer – Defines technical direction, leads cross-portfolio initiatives, designs shared frameworks and scalable AI infrastructure. 
Level and compensation will be determined based on experience and demonstrated expertise. 
 
What We Value 
  • Strong engineering fundamentals 
  • Practical, impact-driven AI development 
  • Curiosity and willingness to experiment responsibly 
  • Ownership mindset and bias toward execution 
  • Ability to balance innovation with reliability 
Why Join Roper 
  • Work on high-impact AI systems across a diverse portfolio of leading software businesses 
  • Build reusable infrastructure that scales across industries 
  • Collaborate with experienced engineering and executive leadership 
  • Shape the next generation of intelligent enterprise software