Data Engineer with ML Ops experience

Data Engineer with ML Ops experience6 MonthsHybrid Working with 2 Days Per Week onsiteInside IR35

My client a top Global company are currently looking to recruit a Data Engineer with ML Ops experience to join their team on a contract basis. Please note if successful you will need to set up via an Umbrella Company/PAYE. The successful Data Engineer with ML Ops experience will execute migration of raw and derived unstructured datasets (images, videos, etc) between on-prem and cloud data locations (e.g. GCP, Azure, AWS). Datasets magnitude vary between small scale (Gb) up to large scale (Tb).

In this role the Data Engineer with ML Ops experience will:

• Execute migration of raw and derived unstructured datasets (images, videos, etc) between on-prem and cloud data locations (e.g. GCP, Azure, AWS). Datasets magnitude vary between small scale (Gb) up to large scale (Tb).
• Ensure consistency between the data ingested and the data manifests.
• Organise raw and derived data into appropriate hierarchies.
• Collaborate with AI/ML engineers and product managers to
  • Develop data pipelines for incoming batch data and update existing pipelines where necessary.
  • Design and implement well decoupled, modularized, reusable, and scalable scripts and code for the retrieval and pre-processing of large-scale histopathology images into the AI/ML pipeline (i.e. each one with order of magnitude of gigabytes)
• Document data flows and ingestion pipelines, data use and re-use
• Implement data flows to connect operational systems, data for analytics and business intelligence (BI) systems (e.g. Power-BI)
• Ensure completion of requisite documentation i.e. ingestion form and any related documentation
• Track & report completion of data migration to stakeholders and raise blockers preventing migration.
• Migrate ML pipelines from on-prem HPC solutions to the cloud.
• Migrate ML pipelines between cloud environments and across cloud computing providers.
• Optimise and parallelise said ML pipelines for scalability, speed and cost efficiency.

We are looking for professionals with these required skills to achieve our goals:

• Experience as a professional data/software engineer.
• Experience of the following: Migrate ML pipelines from on-prem HPC solutions to the cloud; Migrate ML pipelines between cloud environments and across cloud computing providers; and Optimise and parallelise said ML pipelines for scalability, speed and cost efficiency.
• Experience with large-size images and data formats for computational pathology (e.g. .svs, .tiff, .h5) is highly desirable
• Advanced programming expertise in Python and in developing and delivering robust software solutions.
• Machine learning experience
• Computer Vision experience / knowledge.
• CI/CD experience
• Industrial experience in design, development and deployment of data engineering pipelines.
• Experience with cloud platforms, such as Google Cloud Platform, Azure, AWS (preference GCP)
• Experience in handling big data at scale.

Carbon60, Lorien & SRG - The Impellam Group STEM Portfolio are acting as an Employment Business in relation to this vacancy.