What can Machine Learning Architects Basel do for you?
With 10+ years experience in managing highly reliable software projects our team has acquired the conceptual and practical know-how that any organisation aiming towards digital transformation should consider. Together with expert Data Scientists and Machine Learning Engineers we are forming a polyvalent team with a mix of highly experienced consultants, project managers and innovative engineers from different backgrounds to extend our successful concepts of a “Digital Highway for Continuous Software Delivery” and “Effective Site Reliability Engineering (SRE)” to a “Digital Highway for Machine Learning” and “Effective MLOps”.
Machine Learning (ML) systems have a tendency to incur technical debt and get unmanageable. We help our customers address this challenge. With “MLOps” as engineering culture to unify ML system development and operations, we design, build and enable robust, repeatable ML model, data and code pipelines, along with streamlining the way our customers can efficiently develop, test, deploy, monitor, audit, track versions, and reproduce. We call that the “Digital Highway for Machine Learning”.
In line with the Swiss Digital Network’s general approach to transform operating model, technologies as well as culture and skills for a successful Digital Transformation, our offers will cover all these three pillars for our customers to effectively and sustainably leverage all the investments and work they are putting into Data Science and Machine Learning initiatives.
A TRANSVERSAL OFFER TO SUIT ALL YOUR NEEDS
Operating Models & Architecture Designs for MLOps
- Maturity assessments and roadmaps to manage governance, processes and tools
- MLOps and self-service analytics architecture designs for end-to-end ML system development (Dev) and ML system operation (Ops)
- Continuous delivery, observability and model performance management support and guidance to leverage DevOps and Site Reliability Engineering (SRE) principles for Machine Learning
Data Science, Machine Learning, Self-Service & Real-time Analytics Technologies for MLOps
- Customer specific and adapted technology evaluations and roll-outs of:
- Effective MLOps for end-to-end ML system development (Dev) and ML system operation (Ops)
- Self-service & real-time analytics for operations monitoring
- Objective and up-to-date benchmarks of both established market solutions (e.g. Gartner Magic Quadrant for Data Science and Machine Learning) and new, innovative (next generation) tools
Data Science & SRE Trainings for Effective MLOps
- Domain specific offerings of comprehensive, local and cost-effective Data Science trainings for:
- Life Sciences
- Site Reliability Engineering (SRE) trainings by industry practitioners to build end-to-end MLOps skills:
- Public bootcamps
- Enterprise trainings
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Engineering – Architecture – Consulting – Implementation – Training