Synthetic Data Generation SME (Freelancer)

About Us

Deccan AI Experts is a pioneering AI company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in high-quality human-curated data, AI-first operations, and advanced AI evaluation systems.

About the Role

We are seeking a Synthetic Data Generation SME (Freelancer) to support advanced AI evaluation initiatives focused on synthetic data generation, data quality, privacy-preserving AI, machine learning datasets, and benchmark development.

In this role, you will evaluate AI-generated synthetic datasets, data generation pipelines, validation methodologies, and quality assurance processes. Your expertise will help improve AI systems designed for synthetic data creation, dataset augmentation, privacy-safe machine learning, and model evaluation.

This position is ideal for professionals with experience in machine learning, data science, AI research, synthetic data generation, data engineering, or AI benchmarking.

Responsibilities

• Create deliverables addressing real-world synthetic data generation and AI evaluation scenarios.
• Annotate and evaluate AI-generated datasets, synthetic data pipelines, validation reports, and benchmark datasets.
• Assess AI outputs for statistical accuracy, privacy preservation, data quality, and practical usability.
• Design and evaluate synthetic data generation pipelines for structured, semi-structured, or unstructured data.
• Assess whether synthetic datasets accurately match the statistical distributions and characteristics of real-world datasets while maintaining utility.
• Evaluate privacy-safe data generation techniques, ensuring generated data minimizes disclosure risks and supports responsible AI practices.
• Review dataset coverage metrics, diversity, edge-case representation, class balance, and feature completeness.
• Assess quality filtering techniques to detect low-quality, duplicated, biased, inconsistent, or invalid synthetic data.
• Identify statistical inconsistencies, privacy risks, distribution drift, coverage gaps, and data quality issues in AI-generated outputs.
• Provide structured feedback to improve AI performance in synthetic data generation and dataset evaluation workflows.
• Review peer-developed deliverables to maintain quality and consistency standards.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related field.
• PhD in AI, Machine Learning, Data Science, or a related discipline is preferred.
• 3+ years of hands-on experience in synthetic data generation, machine learning, AI research, data science, or data engineering.
• Building and evaluating synthetic data generation pipelines for ML and AI applications.
• Performing distribution matching to ensure statistical similarity between synthetic and real-world datasets.
• Applying privacy-safe data generation techniques, including anonymization, de-identification, differential privacy concepts, or privacy-preserving synthetic data methods.
• Measuring coverage metrics, including class balance, feature diversity, rare case representation, and dataset completeness.
• Implementing quality filtering techniques to identify duplicates, inconsistencies, hallucinations, outliers, bias, and low-quality synthetic records.
• Validating datasets for downstream machine learning performance and benchmark suitability.
• Proficiency in Python and data science libraries such as Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, or similar frameworks.
• Familiarity with synthetic data tools, LLM-based data generation, GANs, VAEs, diffusion models, or data augmentation frameworks is preferred.
• Strong analytical thinking and attention to detail.
• Excellent written English communication skills.
• Ability to critically evaluate AI-generated datasets for statistical validity, privacy compliance, and production readiness.
• Ability to work independently in a remote, fast-paced environment.

Preferred Qualifications

• Experience working with AI research labs, ML platform teams, data engineering organizations, or synthetic data startups.
• Experience developing benchmark datasets for LLMs, computer vision, NLP, recommendation systems, or multimodal AI.
• Familiarity with differential privacy, federated learning, responsible AI, fairness evaluation, and bias mitigation techniques.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for large-scale data processing.
• Contributions to open-source AI, machine learning, or data generation projects are highly desirable.
• Publications or research in synthetic data, machine learning, or AI are an advantage.

Why Join Us

• Competitive hourly pay: ₹1,500/hour
• Fully remote with flexible working hours.
• Opportunity to contribute to cutting-edge AI research and data generation initiatives.
• Exposure to advanced AI systems focused on synthetic data, benchmark creation, and model evaluation.
• Flexible project-based opportunities with global teams.
• Work on next-generation AI solutions supporting privacy-preserving machine learning and responsible AI development.