MLOps Engineer for ML Platform

Think Forward! Our purpose is to empower people to stay a step ahead in life and in business. We are an industry recognized strong brand with positive recognition from customers in many countries, strong financial position, omni-channel distribution strategy and international network. If you want to work at a place with lots of freedom to innovate, where we believe that you can live by the Agile manifesto without jeopardizing the necessary continuity, compliance and QA measures, where we are committed to deliver stable and secure services to end users, and where we have a 'no nonsense' getting-things done mentality, please read on!

What department?

The Analytics Engineering team is a team of 150+ people (and growing rapidly) that has the mission to make ING data driven. We do this by combining Big Data technology with Data Science to deliver high value solutions and products for our organization. We work in a fun and creative environment, and we’re dedicated to bringing out the best in both each other and our projects.

Job description

Your passion is to work with the latest and greatest technologies in the field of Machine Learning Engineering. You will work as a machine learning platformengineer on different projects within the Analytics Engineering, helpingdata scientists train, deploy, monitor and productionizemodels. You will take part in developing and maintaininga data execution platform, keep an eye on good coding practices and create re-usable code.

Do you recognize yourself in this profile:

• Familiar with software engineering practices like versioning, testing, documentation, code review

• Knowledge of MLOps architecture and practices

• Programming inPythonorGo

• Experience with Apache Airflow and MLflow

• Experience in setting up both SQL as well as noSQL databases

• Knowledge of DevOps methodology and tooling

• Experience with monitoring, alerting and observability

• Experience in Kubernetes (deployments and managing Kubernetes applications)

• Experience in building data-oriented platforms

• Relevant work experience in ML or data projects

• Deployment and provisioning automation tools e.g. Docker, CI/CD

Nice to have:

• Experience with distributed systems and clusters for both batch as well as streaming data (S3/Spark/Kafka)

• Hands-on experience building complex data pipelines e.g. ETL

• Basic knowledge of Machine Learning/AI and hands-on technologies and frameworks used in ML

• Bash scripting and Linux systems administration

• Experience with building distributed, large scale and secure applications

• Experience working in cloud environment (e.g. GCP)

• Good understanding of databases including RDBMS

• Experience with working in an agile/scrum way

• Being a committer to Open Source projects is a strong plus

Information about the squad:

We are building cloud ready state of the art Data Analytics Platform to help ING to be even more data driven. This is a joined effort between ING units, and you are going to be part of distributed multi-national and multi-cultural team. There is plenty of work and fun down this road. You can join team of 7 engineers (ML Platform Engineers, MLOps Engineers) that have already delivered Machine Learning Platform on on-prem and starts working on Google Cloud Platform.