We are looking for a specialized Lead Data Intelligence Machine Learning Engineer to design and implement in‑house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques such as Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model‑ready datasets, ensuring high‑quality labels at scale.

• Architect Labelling Pipelines: Design and deploy end‑to‑end automated labelling systems using frameworks such as Snorkel, Cleanlab, or custom active learning loops.
• Develop Human‑in‑the‑Loop (HITL) Systems: Build interfaces and workflows where models pre‑label data and humans only intervene on high‑uncertainty samples.
• Quality Assurance & Denoising: Implement algorithmic checks to identify and correct mislabelled or noisy data within existing datasets.