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Synthetic Data Jobs (NOW HIRING)

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

Responsibilities : • Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

Responsibilities : • Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform ...

Aptive

Data Scientist, Senior

Apply supervised, unsupervised, and reinforcement learning techniques to develop and evaluate data models specific to the healthcare domain, including work with synthetic data models and patient ...

Aptive

Data Scientist, Senior

Apply supervised, unsupervised, and reinforcement learning techniques to develop and evaluate data models specific to the healthcare domain, including work with synthetic data models and patient ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

Allen Control Systems

Platform Engineer, Data

Austin, TX · On-site

$113K - $136K/yr

You'll partner closely with our ML engineers to orchestrate ingestion, synthetic data generation, and versioned releases, ensuring that every dataset is not only high-integrity and available but ...

OpenAI

Researcher, Synthetic RL

San Francisco, CA · On-site

$295K - $445K/yr

About the Team The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores ...

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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.
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Synthetic Data jobs near you
Infographic showing various Synthetic Data job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

AI/Synthetic Engineer

Society for Human Resource Management (SHRM)

Alexandria, VA • On-site

$110K - $135K/yr

Full-time

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.

Job description

SHRM is a member-driven catalyst for creating better workplaces where people and businesses thrive together. As the trusted authority on all things work, SHRM is the foremost expert, researcher, advocate, and thought leader on issues and innovations impacting today's evolving workplaces. With nearly 340,000 members in 180 countries, SHRM touches the lives of more than 362 million workers and their families globally.
Summary
Build the organization's synthetic-audience capability: the data-grounding layer that connects first-party audience data to large language models, the synthetic-audience models themselves, and the engineering pipelines and evaluation harness around them. Direct the synthetic-capability partner and the foundation-model infrastructure beneath it and operate the validation harness that the team will use to judge accuracy. This is an engineering role at heart but applied entirely to research questions.
Responsibilities
  • Design and build the first-party data grounding layer (embeddings / retrieval) that anchors synthetic audiences in real segment data.
  • Build, tune, and maintain synthetic-audience models and the prompt/evaluation pipelines around them.
  • Operate the validation harness: run synthetic output against real holdout data and surface accuracy bounds for the Verification & Validation Data Scientist to interpret.
  • Direct the synthetic-capability partner; manage foundation-model infrastructure and keep the architecture portable across providers.
  • Build guardrails that prevent confident-but-wrong output from reaching stakeholders unflagged.
  • Protect data ownership and ensure member data never trains external shared models.

Education & Experience Requirements
Education
• Bachelor's degree in computer science or related field or relevant equivalent experience in lieu of degree. Master's degree preferred.
Experience
  • Seven (7) or more years in ML/LLM engineering or applied data science, including production systems.
  • Hands-on experience with LLM application development: grounding/RAG, prompt engineering, and evaluation frameworks.
  • Exposure to synthetic data, agent-based simulation, or survey/behavioral data preferred.
  • Experience directing an AI/ML vendor or platform partner preferred.

Certifications - NA
Knowledge, Skills & Abilities
  • Strong data engineering: pipelines, embeddings, working with first-party datasets.
  • Understanding of model evaluation and the failure modes of generative systems.
  • Able to work to research-defined validation standards rather than ship unchecked.
  • Ability to effectively leverage artificial intelligence (AI) tools and technologies to streamline workflows, enhance productivity, and improve overall work quality.

Physical Requirements
This position operates in a typical office environment (which includes a home office setting) and requires the ability to perform essential job functions with or without reasonable accommodation. Physical requirements may include:
  • Prolonged periods of sitting at a desk and working on a computer.
  • Frequent use of hands and fingers for typing, handling documents, and using office equipment.
  • Occasional standing, walking, bending, and reaching.
  • Ability to lift and carry up to 30 pounds as needed.
  • Clear verbal and written communication skills for effective interaction with colleagues and stakeholders.

Work Environment
Hybrid Schedule (3 Days In-Office/2 Days Remote)
This position follows a hybrid work schedule, with Tuesday through Thursday in office and Monday and Friday remote. Employees must be available during standard business hours, with core hours beginning between 8:00-9:00 a.m. and concluding between 5:00-6:00 p.m. local time.
Travel: Occasional 0 - 10%
#LI
The hiring range for this position is $110,000 to $135,000 per year. This range is an estimate, and the actual salary may vary based on the candidate's experience, skills, and qualifications. SHRM offers a competitive and comprehensive total rewards package. The benefits for this position include professional growth and development, health, dental, vision, well-being, health savings, flexible spending, retirement, open leave, and annual discretionary bonus and incentives.
Our employment practices are in accordance with the laws that prohibit discrimination against qualified individuals on the basis of race, religion, color, gender, age, national origin, physical or mental disability, genetic information, veteran's status, marital status, gender identity and expression, sexual orientation, or any other status protected by applicable law.
SHRM is an equal opportunity employer (Minority/Female/Disabled/Veteran).
We do not sponsor applicants for work visas.

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