Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...
Synthetic Data Engineer (AI Data/Training)
Seattle, WA · On-site
$130K - $156K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
Seattle, WA · On-site
$130K - $156K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
San Francisco, CA · On-site
$134K - $162K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
San Francisco, CA · On-site
$134K - $162K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
Boston, MA · On-site
$124K - $149K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
Boston, MA · On-site
$124K - $149K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
San Francisco, CA · On-site
$134K - $162K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
San Francisco, CA · On-site
$134K - $162K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
$130K - $156K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Synthetic Data Engineer (AI Data/Training)
$130K - $156K/yr
In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of ...
Sr Machine Learning Engineer - Synthetic Data & Document Understanding
Austin, TX · On-site
$113K - $136K/yr
Own the synthetic data generation track end-to-end, from architecture to quality validation. * Drive architectural decisions balancing quality, diversity, scale, and cost efficiency. * Define and ...
Sr Machine Learning Engineer - Synthetic Data & Document Understanding
Austin, TX · On-site
$113K - $136K/yr
Own the synthetic data generation track end-to-end, from architecture to quality validation. * Drive architectural decisions balancing quality, diversity, scale, and cost efficiency. * Define and ...
... synthetic data generation capabilities that can be leveraged across programs and products. • Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions ...
... synthetic data generation capabilities that can be leveraged across programs and products. • Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions ...
... synthetic data generation capabilities that can be leveraged across programs and products. • Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions ...
... synthetic data generation capabilities that can be leveraged across programs and products. • Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions ...
Synthetic Data Transformation leader
Chicago, IL · On-site
$130K - $150K/yr
... synthetic data generation capabilities that can be leveraged across programs and products. • Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions ...
Synthetic Data Transformation leader
Chicago, IL · On-site
$130K - $150K/yr
... synthetic data generation capabilities that can be leveraged across programs and products. • Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions ...
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 ...
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 ...
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 ...
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 ...
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 ...
Data Engineer
Buffalo, NY · On-site
$70 - $75/hr
Synthetic data generation * Experience with cloud platforms (Azure strongly preferred) * Ability to work with and across: * Legacy systems * Modern cloud environments * Strong communication skills ...
Data Engineer
Buffalo, NY · On-site
$70 - $75/hr
Synthetic data generation * Experience with cloud platforms (Azure strongly preferred) * Ability to work with and across: * Legacy systems * Modern cloud environments * Strong communication skills ...
Synthetic Data Generation information
See salary details
$31K - $43.5K
12% of jobs
$47.6K is the 25th percentile. Wages below this are outliers.
$43.5K - $56.1K
41% of jobs
$56.1K - $68.6K
4% of jobs
$68.6K - $81.2K
3% of jobs
$81.2K - $93.7K
2% of jobs
$93.7K - $106.3K
0% of jobs
$106.3K - $118.8K
0% of jobs
$118.8K - $131.4K
5% of jobs
$139.5K is the 75th percentile. Wages above this are outliers.
$131.4K - $143.9K
11% of jobs
$143.9K - $156.5K
11% of jobs
$156.5K - $169K
11% of jobs
$31K
$93.2K
$169K
How much do synthetic data generation jobs pay per year?
As of Jul 26, 2026, the average yearly pay for synthetic data generation in the United States is $93,198.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $144,500.00 per year, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive in a Synthetic Data Generation role, and why are they important?
To excel in a Synthetic Data Generation role, you need a solid background in computer science, statistics, and data science, often supported by a relevant degree and experience in machine learning. Familiarity with tools such as Python, TensorFlow, PyTorch, and synthetic data generation platforms, as well as knowledge of privacy-preserving techniques, is typically required. Strong problem-solving abilities, creativity, and effective communication set top performers apart in this field. These skills and qualities are crucial for creating high-quality, realistic synthetic datasets that support robust AI model development while safeguarding sensitive information.
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, machine learning, and programming languages like Python or SQL tend to earn higher salaries.
Which 3 jobs will survive AI?
Synthetic Data Generation specialists are likely to continue being in demand as AI development requires high-quality, labeled data for training models. Roles involving data curation, domain expertise, and oversight of AI systems—such as data scientists, AI ethics officers, and machine learning engineers—are also expected to persist due to their specialized skills and the need for human judgment. These jobs often require technical knowledge, programming skills, and continuous learning to adapt to evolving AI technologies.
What is an example of synthetic data generation?
Synthetic data generation, relevant to roles like data scientists or AI engineers, involves creating artificial data that mimics real datasets using algorithms such as generative adversarial networks (GANs) or statistical models. For example, generating realistic customer transaction records for testing machine learning models without exposing sensitive information. This process helps improve model training while maintaining data privacy and security.
What is synthetic data generation?
Synthetic data generation is the process of creating artificial datasets that mimic real-world data. This technique is used to supplement or replace actual data for purposes such as machine learning, software testing, and research, especially when real data is scarce, sensitive, or costly to obtain. Synthetic data can help improve model accuracy, protect privacy, and enable innovation by providing diverse and unbiased datasets. It is commonly used in fields like healthcare, finance, and autonomous vehicles.
What is the difference between Synthetic Data Generation vs Data Analyst?
| Aspect | Synthetic Data Generation | Data Analyst |
|---|---|---|
| Required Credentials | Knowledge of data science, programming, and data privacy | Degree in statistics, data science, or related field |
| Work Environment | Data science teams, research labs, tech companies | Business environments, analytics teams, consulting firms |
| Industry Usage | AI development, machine learning, data privacy | Business insights, reporting, decision-making |
| Search & Comparison Intent | Understanding data generation techniques, privacy solutions | Analyzing data, generating reports, insights |
While Synthetic Data Generation focuses on creating artificial data for privacy and model training, Data Analysts interpret existing data to provide business insights. Both roles require data-related skills but serve different purposes within the data ecosystem.
What are the main challenges faced by professionals working in synthetic data generation, and how can they be addressed?
Professionals in synthetic data generation often encounter challenges such as ensuring the generated data accurately represents real-world scenarios while maintaining privacy and data security. Balancing realism with anonymization is crucial, especially when synthetic data is used for AI model training or testing. Collaboration with data scientists, domain experts, and privacy officers is common to validate data utility and compliance with regulations. Staying current with advances in generative models and data validation techniques also helps address these challenges and contributes to career growth in this rapidly evolving field.
Is 40 too late for data science?
Age is not a barrier to entering data science or synthetic data generation roles. Many professionals successfully transition into these fields later in life by acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications. Experience, continuous learning, and adaptability are valued more than age in the tech industry.
More about Synthetic Data Generation jobs
What cities are hiring for Synthetic Data Generation jobs? Cities with the most Synthetic Data Generation job openings:
What states have the most Synthetic Data Generation jobs? States with the most job openings for Synthetic Data Generation jobs include:
What job categories do people searching Synthetic Data Generation jobs look for? The top searched job categories for Synthetic Data Generation jobs are:
Nvidia rating
9.6
Based on 17 frontline employees who took The Breakroom Quiz
8th of 245 rated software companies
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 synthetic data generation for training frontier models. You will contribute to open-source libraries within the NVIDIA NeMo ecosystem that generate synthetic datasets across text, code, structured, and multimodal data, directly feeding the pre- and post-training of LLMs such as Nemotron. This role combines hands-on software engineering with applied research in generative methods, and you will collaborate with research, engineering, product, and model teams as well as external labs.
What you'll be doing:
Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning, coding, structured output, and multimodal understanding.
Advance multimodal synthetic data generation - image, document, video, and audio - in partnership with NVIDIA's model teams.
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 3+ years in synthetic data generation, generative modeling, multimodal machine learning, or related areas. Comparable experience is also considered.
Deep technical understanding of LLMs, how data shapes their pre- and post-training, and inference frameworks such as vLLM or TGI.
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:
Open-source contributions in ML or data tooling.
Experience with multimodal generation or understanding (vision-language, document AI, video, or audio).
Building and optimizing scalable data pipelines for large-scale model training (throughput, distributed inference).
Experience generating data for agentic, tool-use, or reinforcement-learning post-training.
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