About the role

We are looking for a specialized 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 like 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.

Key Responsibilities

• Architect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like 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 exi...