... 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 ...
... 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 ...
... graph neural networks for network analysis Experience in design, deployment, support of AI or ML model for significant real-world applications
... graph neural networks for network analysis Experience in design, deployment, support of AI or ML model for significant real-world applications
Experience with graph neural networks for network analysis * Experience in design, deployment, support of AI or ML model for significant real-world applications
Experience with graph neural networks for network analysis * Experience in design, deployment, support of AI or ML model for significant real-world applications
... graph neural networks for network analysis Experience in design, deployment, support of AI or ML model for significant real-world applications About the Organization MRSL is an employee-owned company ...
... graph neural networks for network analysis Experience in design, deployment, support of AI or ML model for significant real-world applications About the Organization MRSL is an employee-owned company ...
Experience with graph neural networks for network analysis * Experience in design, deployment, support of AI or ML model for significant real-world applications About the Organization MRSL is an ...
Experience with graph neural networks for network analysis * Experience in design, deployment, support of AI or ML model for significant real-world applications About the Organization MRSL is an ...
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
Insight into adversarial AI defense, graph neural networks for network topology analysis, or an established track record of shipping end-to-end ML applications to production. Joining StaffRight ...
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
Insight into adversarial AI defense, graph neural networks for network topology analysis, or an established track record of shipping end-to-end ML applications to production. Joining StaffRight ...
Fraud Model Developer
Jacksonville, FL · On-site
... neural networks, clustering analysis) * Experience designing, validating, and monitoring models ... Familiarity with graph databases and network-based fraud detection * Experience developing and ...
Fraud Model Developer
Jacksonville, FL · On-site
... neural networks, clustering analysis) * Experience designing, validating, and monitoring models ... Familiarity with graph databases and network-based fraud detection * Experience developing and ...
Graph Neural Network information
What are the key skills and qualifications needed to thrive in the Graph Neural Network position, and why are they important?
To excel as a Graph Neural Network Engineer, you need a strong background in machine learning, graph theory, neural networks, and proficiency in programming languages such as Python. Familiarity with deep learning frameworks like PyTorch or TensorFlow, and experience with specialized libraries such as DGL or PyTorch Geometric are highly valued. Excellent problem-solving skills, teamwork, and the ability to communicate complex concepts to both technical and non-technical stakeholders will help you stand out. These combined abilities enable professionals to design, implement, and deploy cutting-edge GNN models that address complex, real-world data-structure challenges across various industries.
What does a typical project workflow look like for a Graph Neural Network Engineer?
A typical project workflow for a Graph Neural Network Engineer involves collaborating with data scientists and domain experts to understand the problem, preprocessing and visualizing graph-structured data, and selecting appropriate model architectures. The role often includes building, training, and evaluating GNN models, iterating on hyperparameters, and deploying models to production environments. Throughout the process, you will engage in code reviews, document findings, and present results to stakeholders. Teamwork and effective communication are essential, as projects frequently require close collaboration with researchers, software engineers, and business units to ensure solutions meet practical needs and performance goals.
What is a Graph Neural Network job?
A Graph Neural Network (GNN) job typically involves designing, implementing, and optimizing neural network models that operate on graph-structured data. Professionals in this role apply GNNs to tasks like recommendation systems, fraud detection, social network analysis, and molecular property prediction. Responsibilities often include data preprocessing, model architecture selection, training, evaluation, and deployment. Strong knowledge of machine learning, deep learning frameworks (such as PyTorch or TensorFlow), and graph theory is essential.
What are the most commonly searched types of Graph Neural Network jobs in Florida? The most popular types of Graph Neural Network jobs in Florida are:
What are popular job titles related to Graph Neural Network jobs in Florida? For Graph Neural Network jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Graph Neural Network jobs in Florida look for? The top searched job categories for Graph Neural Network jobs in Florida are:
What cities in Florida are hiring for Graph Neural Network jobs? Cities in Florida with the most Graph Neural Network job openings:
TSI/SSBI/SCI - AI/ML -Software Engineer - Sensing Systems - Sarasota.FL
Henpen CorporationSarasota, FL
Other
Posted 13 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.
- 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.