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Synthetic Data Generation Jobs in California (NOW HIRING)

Humble Robotics

Simulation Engineer

San Francisco, CA · On-site

$100 - $140/hr

You'll build the systems and tools that support closed-loop model testing, synthetic data generation, and sensor simulation. This work will also heavily with modern neural rendering approaches:

Humble Robotics

Simulation Engineer

San Francisco, CA · On-site +1

Develop synthetic data generation workflows, including scenario and agent behavior generation, to support model training * Work closely with ML and autonomy engineers to measure and reduce sim-to ...

Humble Robotics

Simulation Engineer

San Francisco, CA · On-site

Develop synthetic data generation workflows, including scenario and agent behavior generation, to support model training * Work closely with ML and autonomy engineers to measure and reduce sim-to ...

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Synthetic Data Generation information

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 are the key skills and qualifications needed to thrive in synthetic data generation?

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 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.

What is the difference between Synthetic Data Generation vs Data Analyst?

AspectSynthetic Data GenerationData Analyst
Required CredentialsKnowledge of data science, programming, and data privacyDegree in statistics, data science, or related field
Work EnvironmentData science teams, research labs, tech companiesBusiness environments, analytics teams, consulting firms
Industry UsageAI development, machine learning, data privacyBusiness insights, reporting, decision-making
Search & Comparison IntentUnderstanding data generation techniques, privacy solutionsAnalyzing 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 popular job titles related to Synthetic Data Generation jobs in California?

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

What job categories do people searching Synthetic Data Generation jobs in California look for?

The top searched job categories for Synthetic Data Generation jobs in California are:

What cities in California are hiring for Synthetic Data Generation jobs?

Cities in California with the most Synthetic Data Generation job openings:

Synthetic Data Generation jobs near you
Infographic showing various Synthetic Data Generation job openings in California as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Senior Staff Digital World System Engineer

XPENG

Santa Clara, CA • On-site

Full-time

Re-posted 20 days ago

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
Job Responsibilities
  • Be responsible for the overall architecture design and technological evolution of the next-generation synthetic data and Digital World generation system, supporting large-scale model training, simulation and evaluation in the directions of autonomous driving, robotics and embodied intelligence.
  • Lead the construction of core capabilities in directions such as Digital City, Digital Twin, and World Model, and build a high-fidelity, highly scalable virtual world generation and closed-loop simulation system.
  • Be responsible for the R&D of algorithms and systems related to 3D/4D scene reconstruction, including multi-view 3D reconstruction, Gaussian Splatting, NeRF, SLAM/SfM, spatiotemporal scene modeling and other directions, to build large-scale spatial understanding and reconstruction capabilities.
  • Build a synthetic data production engine for perception, prediction, planning, VLA and robot model training, realizing high-quality, high-efficiency and low-cost data generation and delivery.
  • Explore the application of cutting-edge technologies such as Generative AI, Diffusion, World Model and Physics Simulation in the field of simulation and data generation, and promote the evolution of data closed-loop towards automation and intelligence.
  • Build a closed-loop simulation system for Digital City, realizing capabilities such as problem scenario reproduction, model playback verification, long-tail problem mining and automated evaluation.
  • Collaborate in depth with teams of autonomous driving algorithms, robotics, simulation platforms, data Infra and training platforms to promote the integration and large-scale application of synthetic data and real data systems.
  • Define synthetic data quality standards and evaluation systems, continuously optimize authenticity, diversity, generalization and Sim2Real effects, and improve the benefits of model training.
  • Be responsible for the construction of synthetic data platform and team, promote the platformization, engineering and large-scale landing of core technologies, and form long-term evolution capabilities.

Requirements
  • Master's degree or above in Computer Science, Artificial Intelligence, Robotics, Computer Vision, Computer Graphics or related majors.
  • Have R&D experience in related fields such as synthetic data, simulation systems, 3D vision, neural rendering or embodied intelligence.
  • In-depth understanding of technologies related to 3D reconstruction and spatial modeling, including but not limited to SfM, SLAM, NeRF, Gaussian Splatting, Differentiable Rendering, Photogrammetry and other directions.
  • Candidates with relevant project experience in Digital Twin, Digital City, simulation platforms or large-scale virtual scene generation are preferred.
  • Familiar with cutting-edge technology directions such as multi-modal large models, World Model, Generative AI, Diffusion and Reinforcement Learning, and have an in-depth understanding of data-driven model training systems.
  • Have R&D experience in large-scale distributed systems, data generation platforms or high-performance rendering systems, and be able to promote the engineering landing of complex systems.
  • Candidates familiar with Unreal Engine, Unity, Omniverse, physical simulation engines or graphics rendering pipelines are preferred.
  • Have excellent system architecture capabilities and cross-team collaboration capabilities, and be able to promote complex technical projects from research to production landing.
  • Have continuous enthusiasm and technical exploration capabilities in directions such as embodied intelligence, World Model and Digital World generation.

What do we provide:
  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Competitive compensation package.
  • Snacks, lunches, dinners, and fun activities.

The base salary range for this full-time position is $203,450-$344,300, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

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