Data Preparation Engineer

ABOUT THE ROLE

We are looking for a Data Preparation Engineer to build and maintain the datasets that power our machine learning and large language model (LLM) systems. You will turn raw, complex data into clean,well-structured, high-quality training and evaluation data, and own data quality across the ML lifecycle.

KEY RESPONSIBILITIES

Collect, clean, and transform large datasets from diverse sources into ML-ready formats.

Design and maintain reproducible data pipelines for model training and evaluation.

Define and enforce data-quality standards: labeling, deduplication, validation, and versioning.

Ensure correct train/validation/test splits and prevent data leakage.

Curate and structure datasets for model fine-tuning and benchmarking.

Partner with ML engineers and data scientists to diagnose and resolve data-driven model issues.

Document datasets, schemas, and data processes for the wider team.

REQUIRED QUALIFICATIONS

Strong Python and SQL, with experience handling large-scale datasets.

Solid grasp of data-quality, validation, and reproducibility best practices.

Experience preparing data for machine learning or LLM training.

PREFERRED QUALIFICATIONS

Experience with data versioning (DVC, LakeFS) and experiment tracking (Weights & Biases,

MLflow).

Familiarity with cloud data platforms and workflow orchestration (Airflow, Prefect, Dagster).

Experience with labeling/annotation workflows and quality control.

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Required Skills

LLM sql Node.js, Golang, Python

Disclaimer: This job posting & Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.