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Synthetic Data Jobs in Florida (NOW HIRING)

Day to day, you will design simulation environments, produce large volumes of labeled synthetic data, train and evaluate learned policies, and work with engineers across robotics, controls, and ...

Day to day, you will design simulation environments, produce large volumes of labeled synthetic data, train and evaluate learned policies, and work with engineers across robotics, controls, and ...

Develop synthetic data generation pipelines for training perception, manipulation, and navigation models. We're Looking For: * BS, MS, or PhD in Robotics, Computer Science, Mechanical Engineering, or ...

Principal Software Engineer (Python)

Sunrise, FL ยท On-site +1

$128K - $172K/yr

Monitor and provide recommendations on the rapidly evolving AI landscape, including SLM success areas, prompt engineering, and synthetic data generation. * Mentor Senior & Junior Engineers: Act as a ...

Architect scalable test environments, synthetic data solutions, and data pipelines. * Collaborate with cross-functional teams including DevOps to define and implement technology roadmaps. * Establish ...

Senior ML Engineer

Dania Beach, FL

$102K - $141K/yr

Knowledge of synthetic data generation techniques for augmenting fine-tuning datasets. * Exposure to multimodal models (vision-language, speech-language) or voice/speech AI systems. * Contributions ...

Senior Fraud Data Scientist

Miami, FL ยท On-site

$116.25 - $155/hr

Strong expertise in detecting and mitigating fraud risk, including account takeover, synthetic ... data. In the United States, we offer a hybrid work approach at our hub offices, balancing the ...

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Synthetic Data information

What are the key skills and qualifications needed to thrive as a synthetic data engineer, and why are they important?

To thrive as a Synthetic Data Engineer, you need a strong background in computer science, statistics, and data modeling, usually with a degree in a related field. Experience with programming languages like Python or R, familiarity with machine learning frameworks, and knowledge of data privacy tools are essential. Strong analytical thinking, attention to detail, and effective communication help in designing robust data solutions and collaborating with stakeholders. These skills ensure the creation of high-quality synthetic datasets that support research, model training, and compliance with data privacy regulations.

What is the difference between Synthetic Data vs Data Analyst?

AspectSynthetic DataData Analyst
CredentialsNone required, but knowledge of data generation tools helpfulBachelor's degree in data science, statistics, or related field
Work EnvironmentData labs, software development teams, AI/ML projectsBusiness environments, analytics teams, reporting platforms
Industry UsageAI training, testing, privacy complianceData interpretation, reporting, decision support

While Synthetic Data involves creating artificial datasets for testing and training AI models, Data Analysts focus on interpreting real-world data to generate insights. Both roles require data literacy, but Synthetic Data specialists focus on data generation techniques, whereas Data Analysts analyze existing data to inform business decisions.

What are the main challenges faced by professionals working with synthetic data in a production environment?

One of the primary challenges in a synthetic data role is ensuring that the generated datasets accurately reflect real-world scenarios while maintaining privacy and compliance standards. Professionals often need to balance data utility with the risk of introducing bias or unrealistic patterns. Collaboration with data scientists, engineers, and domain experts is essential to validate results and integrate synthetic data into machine learning pipelines. Additionally, staying updated on evolving tools and best practices is crucial for maintaining data quality and relevance.

What is synthetic data and how is it used?

Synthetic data refers to artificially generated information that mimics real-world data but does not contain any actual personal or sensitive details. It is commonly used to train machine learning models, test software, and protect privacy when sharing datasets. By using synthetic data, organizations can avoid data privacy concerns and still gain valuable insights or test algorithms effectively. This approach is especially valuable in industries like healthcare and finance where real data may be restricted. Synthetic data can be generated using various statistical techniques, simulations, or machine learning models.

What are popular job titles related to Synthetic Data jobs in Florida?

For Synthetic Data jobs in Florida, the most frequently searched job titles are:

What cities in Florida are hiring for Synthetic Data jobs?

Cities in Florida with the most Synthetic Data job openings:

Infographic showing various Synthetic Data job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Information Technology_USA - USA_Engineer

Real Soft, Inc.

Jacksonville, FL โ€ข On-site

$106K - $127K/yr

Contractor

This job post hasย expired today.ย Applications are no longer accepted.


Job description

LOCAL to ~MOUNT LAUREL, NJ~ ONLY!
Role Descriptions: TDM EngineerTest Data Management Engineer with expertise in data provisioning| refresh| masking| or orchestrationProven experience in scheduler batch job development (e.g.| Spring Batch or similar frameworks)Experience building RESTful APIs and scalable backend servicesSolid understanding of microservices architecture and enterprise application designStrong SQL and RDBMS knowledge (Oracle| PostgreSQL| MySQL| SQL Server| etc.)hands-on experience with Java and Spring Boot for backend and microservices developmentExperience with build and version control tools (MavenGradle| Git)Familiarity with AgileScrum delivery| CICD pipelines| and production supportExperience working in BFSI or large enterprise environments is a plus
Essential Skills: Data Provisioning| RESTful| SQL| RDBMS
Desirable Skills: 5+ years test data management experienceStrong understanding of data privacy| data classification and data engineering requirementsBuilding data fictionalization| synthetic data creation| data mining| data sub-setting and data conditioning jobsAbility to coordinate and work with different stakeholders to build consensus and deliver outcomesExperience with Topaz| FileAid and Delphix toolsAbility to customize fictionalization solutions between tools and across business applicationsAutomation of processes and jobs via Autosys| CA7| Java| Python| Unix Shell| JCLMainframe: COBOL| DB2| IMS| CICS| VSAM| flat files| EZTrieve| EndevorDistributed Systems: Oracle| msSQLAzure experience with AZ-900 Azure Foundations certification
Keyword: ~5+ years test data management experienceStrong understanding of data privacy| data classification and data engineering requirementsBuilding data fictionalization| synthetic data creation| data mining| data sub-setting and data conditioning jobsAbility to coordinate and work with different stakeholders to build consensus and deliver outcomesExperience with Topaz| FileAid and Delphix toolsAbility to customize fictionalization solutions between tools and across business applicationsAutomation of processes and jobs via Autosys| CA7| Java| Python| Unix Shell| JCLMainframe: COBOL| DB2| IMS| CICS| VSAM| flat files| EZTrieve| EndevorDistributed Systems: Oracle| msSQLAzure experience with AZ-900 Azure Foundations certification~
Skills: MySQL
Experience Required: 8-10, Project Code :