
Data Quality Engineer for AI Systems
4 days ago
We are building at the frontier of Artificial Intelligence (AI), where the quality of data directly defines the power of Large Language Models (LLMs).
As a Lead Data Quality Specialist, you will:
- Automate pipelines that ensure reliability, safety, and relevance of training datasets.
- Run proxy fine-tuning and reward modeling experiments to validate quality.
- Design evaluation frameworks (human + LLM-as-a-judge) to measure consistency and alignment.
- Collaborate with annotation teams to drive scalable, high-quality data workflows.
Key Requirements:
- Strong understanding of LLM training & evaluation (SFT, RLHF, reward models).
- Proficiency in Python, PyTorch, Hugging Face, and evaluation tooling.
- Ability to translate model diagnostics into actionable insights.
- Self-starter with a consultative mindset, comfortable working at the intersection of research and client success.
Benefits of this Role:
- Work on mission-driven AI projects that push the boundaries of model reliability.
- Shape data pipelines that directly influence next-generation AI systems.
- Join a fast-scaling AI-first team with global impact.
This is an opportunity to work where data quality meets model excellence. If you're passionate about data-centric AI, let's discuss further.
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