Generative AI Data Engineer
Algorithms · Full time · Shenzhen (work arrangement discussed for the role)
Compensation discussed individually
Role overview
Design and maintain data processing and quality systems for generative AI training.
Responsibilities
- Design and maintain generative-AI data pipelines across collection, cleaning, preprocessing, sampling, and quality checks.
- Set data cleaning, preprocessing, and quality standards to support usable, consistent, and stable datasets.
- Design data storage and retrieval approaches and build automation that improves processing efficiency and maintainability.
- Work closely with algorithm teams to improve training-data quality, coverage, and iteration speed.
- Contribute to production-grade data pipelines for generative AI.
Requirements
- Bachelor degree or above in computer science, electronic engineering, automation, or a related field.
- Proficiency with Python and sound engineering practice.
- Familiarity with PyTorch, TensorFlow, or comparable deep-learning frameworks and the basics of model training and data management.
- At least two years of data-engineering or ML data-management experience with large-scale processing workflows.
- Strong data-quality awareness and ability to establish practical standards and processes.
Preferred qualifications
- Familiarity with DeepSpeed, vLLM, Megatron, or similar training and deployment tools.
- Experience with generative AI, LLMs, multimodal data processing, or affective computing.
- Experience building data quality systems or automated data toolchains.
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