
Innovative Data Architect
1 week ago
Machine Learning Engineer – Data Quality Lead
Role Overview:As a key member of our team, you will be responsible for ensuring the reliability, safety, and relevance of training datasets through pipeline automation.
This involves running proxy fine-tuning and reward modeling experiments to validate quality, as well as designing evaluation frameworks to measure consistency and alignment.
You will also collaborate with annotation teams to drive scalable, high-quality data workflows that directly influence next-generation AI systems.
Key Responsibilities:- Automate pipelines to ensure reliability, safety, and relevance of training datasets.
- Run proxy fine-tuning and reward modeling experiments to validate quality.
- Design evaluation frameworks to measure consistency and alignment.
- Collaborate with annotation teams to drive scalable, high-quality data workflows.
- 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.
- Opportunity to work on mission-driven AI projects that push the boundaries of model reliability.
- Chance to shape data pipelines that directly influence next-generation AI systems.
- Join a fast-scaling AI-first team with global impact.
If you're passionate about data-centric AI and want to work where data quality meets model excellence, let's talk. Together, we can build innovative solutions that transform industries and improve lives.
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