Build LLM-based methods for synthetic data generation, privacy, and context-aware anonymization, with automated evaluation across multilingual text, documents, and multimodal content. * Optimize task ...
Build LLM-based methods for synthetic data generation, privacy, and context-aware anonymization, with automated evaluation across multilingual text, documents, and multimodal content. * Optimize task ...
We are looking for a hardworking, dedicated, and results-oriented Synthetic Data Engineer. You would join a team using simulation to generate synthetic data. Apple is where individual imaginations ...
We are looking for a hardworking, dedicated, and results-oriented Synthetic Data Engineer. You would join a team using simulation to generate synthetic data. Apple is where individual imaginations ...
You would join a team using simulation to generate synthetic data. Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build ...
You would join a team using simulation to generate synthetic data. Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build ...
Member of Engineering (Pre-training / Synthetic Data)
$117K - $140K/yr
This role particularly focuses on generating synthetic data at scale and determining the best strategies to leverage such data into training large models. You'll closely collaborate with other teams ...
Member of Engineering (Pre-training / Synthetic Data)
$117K - $140K/yr
This role particularly focuses on generating synthetic data at scale and determining the best strategies to leverage such data into training large models. You'll closely collaborate with other teams ...
Physical AI Engineer - Simulation & Synthetic Data Build the Future of Robotics with Physical AI We're building realworld Physical AI systems-where learning agents interact with physical machines.
Physical AI Engineer - Simulation & Synthetic Data Build the Future of Robotics with Physical AI We're building realworld Physical AI systems-where learning agents interact with physical machines.
Physical AI Engineer - Simulation & Synthetic Data Build the Future of Robotics with Physical AI We're building real-world Physical AI systems-where learning agents interact with physical machines.
Physical AI Engineer - Simulation & Synthetic Data Build the Future of Robotics with Physical AI We're building real-world Physical AI systems-where learning agents interact with physical machines.
Data Scientist
Herndon, VA · On-site +1
Generate and analyze synthetic data to augment computer vision models where real-world data is scarce * Train, evaluate, and optimize deep neural network models on overhead imagery, including ...
Data Scientist
Herndon, VA · On-site +1
Generate and analyze synthetic data to augment computer vision models where real-world data is scarce * Train, evaluate, and optimize deep neural network models on overhead imagery, including ...
We are seeking a Simulation Engineer to join our AI robotics research team, focusing on high-fidelity synthetic data generation. In this role, you will leverage classic game engine architecture, 3D ...
We are seeking a Simulation Engineer to join our AI robotics research team, focusing on high-fidelity synthetic data generation. In this role, you will leverage classic game engine architecture, 3D ...
Member of Technical Staff - Simulation (Synthetic Data Generation), Frontier AI & Robotics (FAR)
San Francisco, CA · On-site
We are seeking a Simulation Engineer to join our AI robotics research team, focusing on high-fidelity synthetic data generation. In this role, you will leverage classic game engine architecture, 3D ...
Member of Technical Staff - Simulation (Synthetic Data Generation), Frontier AI & Robotics (FAR)
San Francisco, CA · On-site
We are seeking a Simulation Engineer to join our AI robotics research team, focusing on high-fidelity synthetic data generation. In this role, you will leverage classic game engine architecture, 3D ...
Data Scientist with Security Clearance
Herndon, VA · On-site
$106K - $180K/yr
Generate and analyze synthetic data to augment computer vision models where real-world data is scarce * Train, evaluate, and optimize deep neural network models on overhead imagery, including ...
Data Scientist with Security Clearance
Herndon, VA · On-site
$106K - $180K/yr
Generate and analyze synthetic data to augment computer vision models where real-world data is scarce * Train, evaluate, and optimize deep neural network models on overhead imagery, including ...
Data Scientist
Herndon, VA · On-site
$106K - $180K/yr
Generate and analyze synthetic data to augment computer vision models where real-world data is scarce * Train, evaluate, and optimize deep neural network models on overhead imagery, including ...
Data Scientist
Herndon, VA · On-site
$106K - $180K/yr
Generate and analyze synthetic data to augment computer vision models where real-world data is scarce * Train, evaluate, and optimize deep neural network models on overhead imagery, including ...
This role ensures PI/PHIcompliant synthetic data pipelines, modeltraining readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major changes ...
This role ensures PI/PHIcompliant synthetic data pipelines, modeltraining readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major changes ...
This role ensures PI/PHI-compliant synthetic data pipelines, model-training readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major ...
This role ensures PI/PHI-compliant synthetic data pipelines, model-training readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major ...
This role ensures PI/PHI‑compliant synthetic data pipelines, model‑training readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major ...
This role ensures PI/PHI‑compliant synthetic data pipelines, model‑training readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major ...
Our work combines human and synthetic data techniques, along with other innovative approaches, to capture the nuances of human behavior and use them to steer models. We research and model the ...
Our work combines human and synthetic data techniques, along with other innovative approaches, to capture the nuances of human behavior and use them to steer models. We research and model the ...
AI Research Scientist, Text Data Research - MSL FAIR
Menlo Park, CA · On-site
$184K - $257K/yr
... synthetic data generation, agent and interaction data, and frontier paradigms that redefine what's possible. Based in Meta Superintelligence Labs (MSL) within the Fundamental AI Research Organization ...
AI Research Scientist, Text Data Research - MSL FAIR
Menlo Park, CA · On-site
$184K - $257K/yr
... synthetic data generation, agent and interaction data, and frontier paradigms that redefine what's possible. Based in Meta Superintelligence Labs (MSL) within the Fundamental AI Research Organization ...
Test Data Management Consultant
Little Rock, AR · On-site +1
Integration of Data De-Identification (Delphix) & Synthetic Data tool (GenRocket) into application pipelines Coordinate with offshore team and client stakeholders and ensure all deliverables are ...
Test Data Management Consultant
Little Rock, AR · On-site +1
Integration of Data De-Identification (Delphix) & Synthetic Data tool (GenRocket) into application pipelines Coordinate with offshore team and client stakeholders and ensure all deliverables are ...
Apply synthetic data techniques to support research design, modeling, and data augmentation * Ensure appropriate use of synthetic datasets while maintaining analytical integrity and validity
Apply synthetic data techniques to support research design, modeling, and data augmentation * Ensure appropriate use of synthetic datasets while maintaining analytical integrity and validity
Synthetic Data Generation: Develop and maintain synthetic data generation pipelines to augment evaluation coverage, stress-test safety boundaries, and support evaluation in low-resource languages.
Synthetic Data Generation: Develop and maintain synthetic data generation pipelines to augment evaluation coverage, stress-test safety boundaries, and support evaluation in low-resource languages.
We are looking for a skilled Data Scientist to work closely with our Simulation and Machine Learning Evaluations teams to generate large synthetic datasets, analyze the gap between simulated and real ...
We are looking for a skilled Data Scientist to work closely with our Simulation and Machine Learning Evaluations teams to generate large synthetic datasets, analyze the gap between simulated and real ...
Synthetic Data information
What is the highest paying data job?
In the field of synthetic data, senior roles such as Machine Learning Engineers, Data Scientists, and AI Researchers tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in programming, data modeling, and familiarity with AI tools and frameworks.
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?
| Aspect | Synthetic Data | Data Analyst |
|---|---|---|
| Credentials | None required, but knowledge of data generation tools helpful | Bachelor's degree in data science, statistics, or related field |
| Work Environment | Data labs, software development teams, AI/ML projects | Business environments, analytics teams, reporting platforms |
| Industry Usage | AI training, testing, privacy compliance | Data 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.
Which 3 jobs will survive AI?
Synthetic Data roles, data scientists, and AI/ML engineers are expected to persist as AI advances because they involve designing, managing, and improving AI systems, which require specialized expertise. These jobs often require skills in programming, statistical analysis, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with AI tools and frameworks are essential for long-term job security in these fields.
What is an example of synthetic data?
Synthetic data in the context of a synthetic data job involves artificially generated data that mimics real datasets, such as computer-generated images, text, or numerical information created using algorithms like generative adversarial networks (GANs). It is used to train machine learning models while preserving privacy and reducing bias. Skills in data modeling and familiarity with data generation tools are important for this role.
What is the salary of a synthetic data engineer?
The salary of a synthetic data engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in data modeling, programming, and machine learning tools like Python or TensorFlow tend to earn higher salaries.
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.
More about Synthetic Data jobs
What cities are hiring for Synthetic Data jobs? Cities with the most Synthetic Data job openings:
What states have the most Synthetic Data jobs? States with the most job openings for Synthetic Data jobs include:
What job categories do people searching Synthetic Data jobs look for? The top searched job categories for Synthetic Data jobs are:
Job description
NVIDIA is at the forefront of the AI revolution, and our research is shaping the future of large language models. We are looking for a Senior Scientist to join our team and help advance our capabilities in generating synthetic data and privacy-preserving AI. You will contribute to open-source libraries within the NVIDIA NeMo ecosystem that enable high-quality synthetic data generation and data privacy at scale, including context-aware anonymization. This role combines hands-on software engineering with applied research in LLMs and privacy-enhancing methods, and you will collaborate with research, engineering, product teams, and external labs.
What you'll be doing:
Build LLM-based methods for synthetic data generation, privacy, and context-aware anonymization, with automated evaluation across multilingual text, documents, and multimodal content.
Optimize task-specific LLMs for low-latency, high-throughput inference (distillation, quantization), and scale our frameworks to run in real time.
Design and maintain open-source libraries and SDKs with clean APIs and strong documentation.
Drive software excellence with modern tooling, architecture based on configuration, and professional Git/CI-CD.
Publish original research at top machine learning and AI conferences to maintain NVIDIA's technical leadership.
Mentor interns and junior researchers to develop technical growth within the team.
What we need to see:
PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent experience.
A research background of 2+ years in applied LLM/NLP research and engineering, synthetic data generation, anonymization and PII detection, or related areas. Comparable experience is also considered.
Proven track record of developing or maintaining software libraries used by a broad developer community.
Strong publication record at premier venues such as NeurIPS, ICML, ICLR, ACL or similar.
Ways to stand out from the crowd:
Active contributions to open-source projects, particularly in ML, security, or privacy domains.
Deep technical understanding of LLMs and inference optimization (quantization, distillation, latency/throughput tuning), with frameworks such as vLLM or TGI.
Ability to build and optimize scalable data processing pipelines for large-scale models.
Functional knowledge of global privacy regulations such as GDPR or CCPA.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and talented people in the world working with us. If you are creative, autonomous, and passionate about building open-source tools that make AI safer and more private, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 3, and 192,000 USD - 304,750 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
About Nvidia
Sourced by ZipRecruiter
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Santa Clara, CA, US
Year founded
1993