... machine learning models and large language models. • Conduct research to provide technical ... testing, and deployment methodology based on business and security requirements. • Work closely ...
... machine learning models and large language models. • Conduct research to provide technical ... testing, and deployment methodology based on business and security requirements. • Work closely ...
AI Data Engineer - Manager
Tampa, FL · On-site
... machine learning models and large language models. • Conduct research to provide technical ... testing, and deployment methodology based on business and security requirements. • Work closely ...
AI Data Engineer - Manager
Tampa, FL · On-site
... machine learning models and large language models. • Conduct research to provide technical ... testing, and deployment methodology based on business and security requirements. • Work closely ...
AI Data Engineer Manager
Jacksonville, FL · On-site
... machine learning models and large language models. • Conduct research to provide technical ... testing, and deployment methodology based on business and security requirements. • Work closely ...
AI Data Engineer Manager
Jacksonville, FL · On-site
... machine learning models and large language models. • Conduct research to provide technical ... testing, and deployment methodology based on business and security requirements. • Work closely ...
Senior Data Scientist
Fort Lauderdale, FL · On-site
Build statistical and machine learning models to improve content discovery and user engagement ... Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze ...
Senior Data Scientist
Fort Lauderdale, FL · On-site
Build statistical and machine learning models to improve content discovery and user engagement ... Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze ...
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Full Sail University is seeking faculty with expertise in Artificial Intelligence, Machine Learning ... Additional focus will be placed on HCI principles such as user-centered design, usability testing ...
Full Sail University is seeking faculty with expertise in Artificial Intelligence, Machine Learning ... Additional focus will be placed on HCI principles such as user-centered design, usability testing ...
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AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
$135K - $180K/yr
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Quick apply
Be Seen First
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
$135K - $180K/yr
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Be Seen First
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
$135K - $180K/yr
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Quick apply
Be Seen First
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
$135K - $180K/yr
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Be Seen First
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
$135K - $180K/yr
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Quick apply
Be Seen First
AI/ML Software Engineer - TS/SCI
Sarasota, FL · On-site
$135K - $180K/yr
... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...
New
Machine learning algorithms, including natural language processing (NLP) techniques; * Foundation in statistical methods such as hypothesis testing, confidence intervals, and regression analysis;
Machine learning algorithms, including natural language processing (NLP) techniques; * Foundation in statistical methods such as hypothesis testing, confidence intervals, and regression analysis;
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
Quick apply
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
Quick apply
In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...
Data Scientist
Saint Petersburg, FL · On-site
$137K/yr
Machine learning algorithms, including natural language processing (NLP) techniques; * Foundation in statistical methods such as hypothesis testing, confidence intervals, and regression analysis;
Data Scientist
Saint Petersburg, FL · On-site
$137K/yr
Machine learning algorithms, including natural language processing (NLP) techniques; * Foundation in statistical methods such as hypothesis testing, confidence intervals, and regression analysis;
... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...
New
... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...
New
... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...
New
... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...
New
... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...
New
... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...
New
Machine Learning Testing information
See Florida salary details
$10.42 - $11.58
3% of jobs
$11.58 - $12.74
7% of jobs
$12.74 - $13.90
6% of jobs
$14.77 is the 25th percentile. Wages below this are outliers.
$13.90 - $15.06
11% of jobs
$15.06 - $16.22
13% of jobs
The median wage is $16.83 / hr.
$16.22 - $17.38
18% of jobs
$17.38 - $18.54
16% of jobs
$18.61 is the 75th percentile. Wages above this are outliers.
$18.54 - $19.70
9% of jobs
$19.70 - $20.85
6% of jobs
$20.85 - $22.01
7% of jobs
$22.01 - $23.17
3% of jobs
$10
$17
$23
How much do machine learning testing jobs pay per hour?
As of May 30, 2026, the average hourly pay for machine learning testing in Florida is $17.05, according to ZipRecruiter salary data. Most workers in this role earn between $14.71 and $19.04 per hour, depending on experience, location, and employer.
What is a Machine Learning Testing job?
A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.
What are the key skills and qualifications needed to thrive in the Machine Learning Testing position, and why are they important?
To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.
What are the typical challenges faced by professionals in Machine Learning Testing roles?
Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.
More about Machine Learning Testing jobs
What are the most commonly searched types of Machine Learning Testing jobs in Florida? The most popular types of Machine Learning Testing jobs in Florida are:
What are popular job titles related to Machine Learning Testing jobs in Florida? For Machine Learning Testing jobs in Florida, the most frequently searched job titles are:
- Machine Learning Specialist
- Senior Machine Learning Engineer Biotech
- Remote Prototype Machinist
- Scientific Machine Learning
- Manager Remote Machine Learning Engineer
- Senior Applied Scientist Machine Learning
- Machine Learning Scientist
- Remote Machine Learning Finance
- Freelance Machine Learning Data Annotation
- Data Science Machine Learning
What job categories do people searching Machine Learning Testing jobs in Florida look for? The top searched job categories for Machine Learning Testing jobs in Florida are:
- Freelance Artificial Intelligence Machine Learning
- Learning Disability
- Freelance Bioinformatics Machine Learning
- Remote Machine Learning Ops Engineer
- Remote Machine Learning Quant
- Machine Learning Internship Microsoft
- Physics Informed Machine Learning
- Associate Machine Learning Chemistry
- Senior Meta Machine Learning
- Senior Data Scientist Citizen
Deloitte rating
8.1
Based on 86 frontline employees who took The Breakroom Quiz
59th of 138 rated financial services
Job description
Job Summary:
Deloitte is a leading consulting firm focused on transforming the nature of work through innovative solutions. They are seeking an AI Data Engineer - Manager to lead data architecture and engineering delivery for AI/ML/GenAI solutions, ensuring data integrity and scalability while managing a team and collaborating with various stakeholders.
Responsibilities:
• Lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption.
• Design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data.
• Manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.
• Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
• Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases.
• Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
• Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
• Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
• Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
• Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
• Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
• Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
• Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
• Be responsible for the successful execution of AI-powered applications using agile methodology.
• Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
• Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
• Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
• Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
• Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
• Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
• 6+ years of consulting experience leading delivery teams, including onshore and offshore team members
• 6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
• 5+ years of experience working in an AI environment
• 5+ years of experience translating requirements into client ready design documents
• 5+ years of experience in software application architecture analysis, design, and delivery
• 5+ years of experience executing full system development life cycle implementations
• Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.
Preferred:
• Advanced degrees such as Masters or PhD are preferred
• Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
• 5 + years of experience in Data Science, Statistics, and Machine Learning
• 5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
• 5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
• 5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.
Deloitte is a leading consulting firm focused on transforming the nature of work through innovative solutions. They are seeking an AI Data Engineer - Manager to lead data architecture and engineering delivery for AI/ML/GenAI solutions, ensuring data integrity and scalability while managing a team and collaborating with various stakeholders.
Responsibilities:
• Lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption.
• Design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data.
• Manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring.
• Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
• Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases.
• Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
• Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
• Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
• Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
• Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
• Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
• Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
• Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
• Be responsible for the successful execution of AI-powered applications using agile methodology.
• Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
• Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
• Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
• Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
• Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
• Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
• 6+ years of consulting experience leading delivery teams, including onshore and offshore team members
• 6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
• 5+ years of experience working in an AI environment
• 5+ years of experience translating requirements into client ready design documents
• 5+ years of experience in software application architecture analysis, design, and delivery
• 5+ years of experience executing full system development life cycle implementations
• Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.
Preferred:
• Advanced degrees such as Masters or PhD are preferred
• Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
• 5 + years of experience in Data Science, Statistics, and Machine Learning
• 5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
• 5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
• 5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.