Machine Learning Engineer – Data Analyst

About the role

We are seeking a Machine Learning Engineer who will also function as a Data Analyst. The role focuses on building and maintaining data platforms, distributed processing pipelines, and scalable feature stores, while supporting the end‑to‑end machine‑learning lifecycle from model training to production monitoring.

Key responsibilities

• Assist in developing components for a data platform that supports distributed pipelines and feature stores, including data health monitoring and alerts.
• Support ML platform components for distributed model training, evaluation, observability, and performance monitoring.
• Help implement end‑to‑end MLOps pipelines and provide production support for data scientists and data engineers.
• Generate last‑mile data readiness (e.g., embeddings) to enable rapid model application on curated features.
• Apply machine‑learning techniques in collaboration with data scientists and domain experts, including unsupervised methods such as clustering.
• Contribute to the selection, acquisition, and integration of AI‑focused data components for analysis.
• Perform exploratory data analysis, data design, modelling, and quality assurance to maintain highly curated features.
• Facilitate physical database and data‑warehouse designs to ensure feature availability for the model development lifecycle.
• Ensure data accessibility, retrievability, security, and ethical handling.
• Design, code, test, document, and refactor moderately complex programs/scripts, supporting CI/CD practices for feature engineering and model training/inferencing.
• Build cloud/on‑premise MDLC templates to orchestrate development processes across engineering teams.

Required profile

• Ability to collaborate with data scientists and data engineers to productionise pipelines and models.
• Strong analytical mindset for data readiness and feature curation.
• Experience with distributed data processing and model monitoring concepts.

Required skills