N-iX is looking for a mid-level Data Engineer with ML experience to deploy production ML models at a significant scale.

As part of the data licensing team, you will work closely with data science and data engineering colleagues to apply state-of-the-art models in production.

Projects will vary from deploying models that provide new metadata for the existing catalogue to developing novel techniques for asset retrieval. Given the magnitude of data and AI focus, this role presents unique and exciting opportunities that have an immediate revenue impact.

Our customer is a technology company that powers one of the world's largest two-sided marketplaces for high-quality photos, illustrations, videos and music used by individuals, businesses, marketing agencies and media organisations of all sizes.

Responsibilities:
- Work with data scientists to design scalable ML pipelines that integrate into existing architecture.

- Under the guidance of a principal engineer, take ownership of all ML ops and data engineering deliverables for an assigned project.

- Support the deployment of models into production environments (batch and/or real-time), including containerization, inference orchestration, and integration with relevant tools and services.

- Build internal tools (e.g., Streamlit apps) to showcase ML outputs.

Requirements
Essential:
- Experience designing and implementing large-scale cost cost-effective production workflows within AWS (lambda, kafka, kinesis, EKS, step functions)
- Experience working with data scientists to transition notebooks (Databricks, Sagemaker) into production code.
- Python
- Pipeline Orchestration, ideally Airflow.

Nice to have:
- MLFlow
- DBT
- Frontend Experience
- Spark / PySpark