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Neural Network Engineer Jobs in Florida (NOW HIRING)

AI/ML Engineer

Fort Lauderdale, FL · On-site

$109K - $131K/yr

... neural network architectures for complex data patterns. • Build, optimize, and consume scalable REST APIs to seamlessly integrate AI/ML models into production software environments. • Structure ...

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Neural Network Engineer information

See Florida salary details

$23.2K

$81.5K

$118.1K

How much do neural network engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for neural network engineer in Florida is $81,484.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $99,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Neural Network Engineer position, and why are they important?

To thrive as a Neural Network Engineer, you need a strong background in machine learning, deep learning frameworks (such as TensorFlow or PyTorch), and proficiency in programming languages like Python or C++. Experience with GPU computing, cloud-based machine learning platforms, and relevant certifications (e.g., TensorFlow Developer Certificate) is often valuable. Strong problem-solving skills, teamwork, and effective communication help you excel when collaborating on complex AI models and projects. These abilities are essential for designing effective neural networks, integrating them into products, and driving innovation in real-world applications.

What are the common daily responsibilities of a Neural Network Engineer?

On a typical day, a Neural Network Engineer may design and test deep learning model architectures, preprocess data, write and optimize code, and analyze performance results. Collaborating closely with data scientists, software engineers, and product managers is common to align model development with business objectives. Engineers often participate in code reviews, debugging sessions, and contribute to technical documentation. Staying current with the latest research and integrating new approaches is also part of the role, ensuring that solutions are both cutting-edge and practical for deployment.

What does a Neural Network Engineer do?

A Neural Network Engineer designs, develops, and optimizes machine learning models, particularly artificial neural networks, to solve complex problems. They work with deep learning frameworks like TensorFlow and PyTorch, train and fine-tune models, and optimize them for performance and efficiency. Their role often involves preprocessing data, selecting appropriate architectures, and deploying models in real-world applications such as computer vision, natural language processing, or autonomous systems.

What are the most commonly searched types of Neural Network Engineer jobs in Florida? The most popular types of Neural Network Engineer jobs in Florida are:
Infographic showing various Neural Network Engineer job openings in Florida as of June 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $81,484 per year, or $39.2 per hour.

TSI/SSBI/SCI - AI/ML -Software Engineer - Sensing Systems - Sarasota.FL

Henpen Corporation

Sarasota, FL

Other

Posted 20 days ago


Job description

Must be TSI/SSBI/SCI to move forward. if not, your application will not be considered.
- AI/ML Software Engineer

Sarasota, Florida, USA
Job Description
We are looking for an engineer with a solid foundation in artificial intelligence and machine learning applications to help us solve challenging problems related to signal processing.
The right candidate will have a high degree of drive and dedication, and the ability to learn quickly, work well within a team, and hit the ground running.
BS degree or higher in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, or related fieldMinimum 1-year hands-on experience in AI or ML in a professional environment (3-5 years preferred)Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.)Solid programming background with experience using statistical and signal analysis librariesExperience with neural network architectures including deep learning modelsUnderstanding of transformer architectures and attention mechanismsStrong understanding of MLOps, deployment and processing pipelines, testing/validationTS/SCI active clearance required. U.S. Citizenship required
Nice to have, but not required:Understanding of digital signal processing fundamentalsExperience with RFMLExperience with Large Language Models (LLMs) including fine-tuning and prompt engineeringKnowledge of AI applications for autonomous decision-making and analysisAdditional consideration for experience with multimodal, agentic systems using RAG, COT, or MARL approachesExperience with reinforcement learning, human feedback, and related system learning methodsExperience creating and deploying containerized AI models with Docker/KubernetesWorking with cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI)Experience with model monitoring, A/B testing, and performance optimizationExperience with real-time inference systems and low-latency model servingKnowledge of adversarial ML and AI security/robustness techniquesExperience with graph neural networks for network analysisExperience in design, deployment, support of AI or ML model for significant real-world applications
Job Duties:
You will be responsible for designing, developing, and implementing AI/ML solutions for a wide range of decision-making and SIGINT processing needs.
This includes working with time-series data and developing models for event characterization, pattern recognition, anomaly detection, decision making, and automated analysis of SIGINT sensor systems.
You will work with team leads to integrate AI/ML capabilities into enterprise architectures, ensuring performant processing while considering aspects of accuracy, security, and maintainability.
This also includes enabling autonomous decision-making systems that can operate with minimal human intervention, creating adaptive processing systems for dynamic environments, and discovering features and inferring system states from the underlying data streams.
You will work towards solutions for large-scale sensing systems, implementing tailored models deliver intelligent insights in support of critical Intelligence Community and Department of Defense missions.
FULL RELOCATION plus Industry best benefits & stock.
Qualifications
BS degree or higher in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, or related field
Minimum 1-year hands-on experience in AI or ML in a professional environment (3-5 years preferred)
Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.)
Solid programming background with experience using statistical and signal analysis libraries Experience with neural network architectures including deep learning models Understanding of transformer architectures and attention mechanisms
Strong understanding of MLOps, deployment and processing pipelines, testing/validation
TS/SCI active clearance required.
U.S. Citizenship required
Nice to have, but not required: Understanding of digital signal processing fundamentals
Experience with RFML Experience with Large Language Models (LLMs) including fine-tuning and prompt engineering
Knowledge of AI applications for autonomous decision-making and analysis
Additional consideration for experience with multimodal, agentic systems using RAG, COT, or MARL approaches
Experience with reinforcement learning, human feedback, and related system learning methods
Experience creating and deploying containerized AI models with Docker/Kubernetes
Working with cloud AI platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI)
Experience with model monitoring, A/B testing, and performance optimization
Experience with real-time inference systems and low-latency model serving
Knowledge of adversarial ML and AI security/robustness techniques
Experience with graph neural networks for network analysis
Experience in design, deployment, support of AI or ML model for significant real-world applications
Job Duties:
You will be responsible for designing, developing, and implementing AI/ML solutions for a wide range of decision-making and SIGINT processing needs.
This includes working with time-series data and developing models for event characterization, pattern recognition, anomaly detection, decision making, and automated analysis of SIGINT sensor systems.
You will work with team leads to integrate AI/ML capabilities into enterprise architectures, ensuring performant processing while considering aspects of accuracy, security, and maintainability.
This also includes enabling autonomous decision-making systems that can operate with minimal human intervention, creating adaptive processing systems for dynamic environments, and discovering features and inferring system states from the underlying data streams.
You will work towards solutions for large-scale sensing systems, implementing tailored models deliver intelligent insights in support of critical Intelligence Community and Department of Defense missions.
FULL RELOCATION plus Industry best benefits & stock.
Why is This a Great Opportunity
We are looking for an engineer with a solid foundation in artificial intelligence and machine learning applications to help us solve challenging problems related to signal processing.
The right candidate will have a high degree of drive and dedication, and the ability to learn quickly, work well within a team, and hit the ground running.