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Machine Learning Software Engineer Jobs in Florida

kgs

Software Engineer

Cape Canaveral, FL · On-site

The Software Engineer will be responsible for designing, implementing, and maintaining complex ... Machine learning/AI concepts * Performance optimization techniques * Enterprise architecture ...

Cliftonlarsonallen

Senior AI Engineer

Naples, FL · On-site

$98K - $135K/yr

This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI ...

Bespoke Labs

Machine Learning Engineer

Orlando, FL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Melbourne, FL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Fort Myers, FL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Tampa, FL · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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All JobsMachine Learning Software Engineer JobsMachine Learning Software Engineer Jobs in Florida

Machine Learning Software Engineer information

See Florida salary details

$47.5K

$110.2K

$153.6K

How much do machine learning software engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning software engineer in Florida is $110,243.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,700.00 and $129,300.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

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

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.

What are the most commonly searched types of Machine Learning Software Engineer jobs in Florida? The most popular types of Machine Learning Software Engineer jobs in Florida are:
What are popular job titles related to Machine Learning Software Engineer jobs in Florida? For Machine Learning Software Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Machine Learning Software Engineer jobs in Florida look for? The top searched job categories for Machine Learning Software Engineer jobs in Florida are:
What are popular job titles related to Machine Learning Software Engineer jobs in FL? For Machine Learning Software Engineer jobs in FL, the most frequently searched job titles are:
Machine Learning Software Engineer jobs near you
Infographic showing various Machine Learning Software Engineer job openings in Florida as of July 2026, with employment types broken down into 90% Full Time, 6% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $110,243 per year, or $53 per hour.

AI Software Engineer

Cooperidge Consulting Firm

Sarasota, FL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Cooperidge Consulting Firm is seeking an AI/ML Software Engineer for a premier Defense & Intelligence Technology leader in Sarasota, FL.
This role is designed for a high-drive engineer with a deep foundation in artificial intelligence and its practical application to complex signal processing. You will be responsible for designing and deploying AI/ML solutions that address critical SIGINT (Signals Intelligence) processing needs, including time-series data analysis and autonomous decision-making. Working within a high-stakes environment, you will build adaptive systems for the Department of Defense (DoD), ensuring that machine learning architectures can operate with elite accuracy, security, and low-latency inference in dynamic mission environments.
Job Responsibilities
  • SIGINT Processing: Design and implement AI/ML models for event characterization, pattern recognition, and anomaly detection within high-volume sensor data streams.
  • Autonomous Decision-Making: Enable intelligent systems that operate with minimal human intervention, focusing on adaptive processing and system-state inference.
  • Enterprise Integration: Partner with team leads to integrate AI/ML capabilities into large-scale enterprise architectures, prioritizing performant processing and maintainability.
  • Architecture Development: Utilize Transformers, attention mechanisms, and deep learning architectures to discover features within time-series and RF data.
  • MLOps Oversight: Own the deployment and processing pipelines, ensuring rigorous testing, validation, and security of containerized models.
  • Real-World Impact: Develop tailored models to deliver intelligent insights in support of high-priority missions for the Intelligence Community.
  • Feature Discovery: Infer system states from underlying data streams to support critical analysis of sensor systems.

Requirements
Education & Legal
  • BS degree or higher in Computer Science, Electrical Engineering, Mathematics, or a related field.
  • ACTIVE TS/SCI Clearance is REQUIRED.
  • U.S. Citizenship is REQUIRED.
Experience
  • Minimum of 1 year of professional AI/ML experience (3-5 years preferred).
  • Proven expertise in model development and deployment using modern libraries (TensorFlow, PyTorch, scikit-learn).
  • Strong background in neural network architectures, including deep learning and transformers.
  • Solid programming skills with experience in statistical and signal analysis libraries.
  • Deep understanding of MLOps, deployment pipelines, and testing/validation protocols.
Nice-to-Have (Bonus Skills)
  • Experience with RFML (Radio Frequency Machine Learning) or Digital Signal Processing.
  • Familiarity with LLMs, RAG, Agentic systems, or Reinforcement Learning (RLHF).
  • Proficiency with Docker/Kubernetes and cloud platforms (AWS Bedrock, Azure OpenAI, Vertex AI).
  • Experience with real-time inference, low-latency model serving, or adversarial ML.

Benefits
  • Comprehensive health, vision, and dental insurance plans
  • Life insurance coverage
  • 401(k) retirement plan with company matching contributions
  • Paid time off including vacation, sick leave, and holidays
  • Opportunities for career growth and advancement

Apply