Our client, a multinational energy company, wanted to learn more about Machine Learning Operations (MLOps) in order to see if it could present any opportunities for their business.
The Pangea SI team sourced MLOps Engineering Experts within a 48-hour timeframe who had:
- Long term experience in front end engineering: conceptualising, development, productionalising and scaling of real-world ML use cases.
- Hands-on experience in designing, using and operating comprehensive ML platforms for automating the complete ML lifecycle.
- Extensive expertise in ML Engineering and MLOps utilising Azure ML and Azure DevOps with strong focus on modularization, reusability, reproducibility, tracking of ML pipelines.
- Long-standing expertise in design and operations of containerized ML environments and applications.
- Long-term experience with public Cloud platform, in particular Azure.
These Experts included:
• Senior Technical Lead of Big Data Platform Engineering (Cloudera), Azure ML & DevOps, MLOps, Stream Analytics - 20+ years of IT industry experience, focusing on practice development, delivery excellence and solution definition. Expert has experience working with key customers across the globe (US, UK, Europe, Australia and Asia) in the areas of: Data Warehousing, Big Data Platform Engineering (MapR & Cloudera), Azure/AWS Cloud, Azure DevOps, Business Intelligence (BI) and Data Science.
• The owner and Cloud Architect (Azure DevOps & MLOps) of a company specialising in Azure and Azure DevOps – a Microsoft Certified Azure DevOps Engineer Expert, Azure Solutions Architect Expert And Azure Administrator Associate, having designed architecture for one of the biggest projects in the U.K. on Azure, assisting the firm to secure a multi-million project.
• Artificial Intelligence Architect/AI Engineering Lead – a Civil Engineer in computer science with 14 years’ total experience, with main interests focused on data modelling and engineering. Expert has 2 years’ experience in automotive industries, 8 years’ in telecoms, 1 ½ years’ in banking and payments (detecting fraud and spam), 3+ years on healthcare (patient data etc.).
Rapid Insights: The client was able to clearly and effectively explore how they could implement MLOps to drive their business further.