Confidential
Hybrid (Flexible / Intentional)
Belgium
Posted 4 days ago
Company: Confidential
Location: Remote / Hybrid / Paris, France
Employment Type: Full-time
Department: Data Science & Machine Learning
About the Role
We are hiring a Synthetic Data Engineer to design and build automated data pipelines that generate high-fidelity artificial datasets. You will help train and fine-tune machine learning models where real-world data is scarce, expensive, or restricted by privacy regulations.
Key Responsibilities
- Data Generation: Utilize generative models (GANs, VAEs, Diffusion Models, or LLMs) to synthesize realistic structured, text, or image datasets.
- Validation & Quality Control: Perform statistical evaluations to ensure synthetic data accurately mirrors real-world distributions while preventing mode collapse.
- Privacy Assurance: Apply differential privacy and anonymization techniques to guarantee zero leakage of personally identifiable information (PII).
- Data Pipeline Engineering: Build scalable, repeatable data generation and ingestion pipelines using Python, SQL, and orchestration tools like Airflow.
Qualifications & Requirements
- 3+ years in Data Engineering, Data Science, or Machine Learning with expertise in Python and SQL.
- Strong statistical background (distribution analysis, hypothesis testing, generative modeling).
- Experience with privacy-preserving frameworks and synthetic data tools.
- Experience with large-scale data storage and compute engines (e.g., Spark, Snowflake).
Offer
- Competitive base salary and performance incentives.
- Flexible work arrangements and home office setup allowance.
- Continuous learning budget for research and technical books/courses.