Your areas of expertise
You have a successful track record working with teams at a SaaS company.
You worked with machine learning teams and participated in the design and development of ML Ops architecture for both training and inference infrastructure.
You have an experience with at least one of the ML Ops frameworks (Kubeflow, MLflow, SageMaker, etc.)
You have knowledge of common programming languages, concepts, and architectures (Python in particular).
You have previous system design experience with respect to new application services on AWS (or other cloud providers), you worked with CI/CD, Terraform, and Kubernetes
You are familiar with Airflow and Spark.
You have experience with distributed infrastructure technologies in areas such as container orchestration, service mesh & tracing, centralised logging/monitoring/metrics.
You have experience defining a general data- & analytics strategy.
You have a proficient level of spoken and written English.
You have a strong sense of ownership and ability to operate autonomously.
You will be working with various stakeholders within i2x (CTO, Product manager & engineers) to shape the future of our cloud platform by designing and building a robust and sustainable ML Ops infrastructure.
While actively coding yourself, you will provide guidance to the research and software engineers by creating technical design documents, educating and reviewing others code.
What you can expect from us
- Working with international, highly engaged people.
- We are agile in a genuine sense of it, being holistic and humane in the way we approach our work.
- We love solid engineering, independent thinking, being on the edge of science and technology, questioning the existing state of things.
- Be part of a growing team making fast decisions, where you can watch your ideas and actions come to fruition.
- Work-family-friends balance – step off the treadmill and feel like a human again.
- Choice of hardware.