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3 days ago
We are building at the frontier of AI, where data quality directly defines the power of Large Language Models (LLMs). In this role, you will lead data quality initiatives that drive model reliability and excellence.
Your key responsibilities will include:
- Automating pipelines to ensure the reliability, safety, and relevance of training datasets.
- Designing evaluation frameworks to measure consistency and alignment.
- Collaborating with annotation teams to drive scalable, high-quality data workflows.
You will work closely with our engineering team to integrate your efforts into our existing infrastructure. We offer a dynamic work environment with opportunities for growth and professional development.
About This RoleThis is an exciting opportunity to work on mission-driven AI projects that push the boundaries of model reliability. You will have the chance to shape data pipelines that directly influence next-generation AI systems.
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.
- A fast-scaling AI-first team with global impact.
- Mission-driven work on AI projects that make a difference.
- Opportunities for growth and professional development.
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