Machine Learning Engineer
October 20
Airflow
Azure
Cloud
Docker
Grafana
Java
JavaScript
Kotlin
Kubernetes
OpenShift
Postgres
Prometheus
Python
Vue.js
Go
Description
• Join us as a Machine Learning Engineer in our Data Platform Team. • We take care of transforming raw data into a strategic core asset. • Build, operate and continuously improve (MLOps) scalable machine learning models. • Work with data scientists, data engineers, and a data solution architect. • Design and develop AI services from PoCs to production. • Responsible for the development and maintenance of ML infrastructure code. • Deploy machine learning models into production environments using CI/CD pipelines. • Collaborate with DevOps for infrastructure selection & setup.
Requirements
• You have working experience as a ML or Data Engineer with a strong understanding of AI/ML concepts. • You possess proficient OOP skills (Python) and a deep understanding of ML engineering and Ops concepts such as: Data pre-processing/feature engineering automation, Batch/stream serving, Pipeline orchestration, Experimentation/versioning and reproducibility. • You are able to bring prototypes into production mode and operate machine learning pipelines using containerisation & orchestration technologies (Docker, Kubernetes) as well as version control, CI/CD & open-source MLOps tools like GitLab, ClearML/MLflow/Airflow, DVC, Kubeflow. • If you also have experience e.g. in cloud platforms (Google Cloud/Azure), model monitoring & logging (Grafana/Prometheus), some notions of Data Engineering – that would be great! • You feel comfortable collaborating in cross-functional teams with data scientists, developers, DevOps & stakeholders and you have strong problem-solving and communication skills. • You are eager to learn and adopt new ML/AI technologies and lead, mentor junior colleagues. • Proficiency in English (C-Level) is essential for this role, as you will collaborate with diverse stakeholders. • Skills in German, Spanish or Bulgarian are a plus.
Benefits
• Flexible instead of nine to five - mobile working and workation • Flexible working hours, different part-time models - all this is possible with us. • We live the work-life balance - e.g. with a minimum of 25 days paid annual leave plus 5 additional days off if desired. • We #takecare - We support your voluntary work with an extra day of vacation and actively support climate protection projects. • Come as you are - No dress code in a humorous, appreciative team culture. • Celebrate with us - Nexie team evenings, unusual summer & winter events. • Top Tech-Stack - Work with modern technologies and methods such as Vue.js, Java & Kotlin, Docker, OpenShift, PostgreSQL, and much more! • Feel at home in the office - Quiet Space, foosball rounds, joint nexMampfs, fresh fruit and latte macchiato are a matter of course for us. • Your health is important to us - be on the road with BusinessBike and become a member of EGYM Wellpass with over 6,500 training options. • Develop yourself further with us - We support your personal and professional development - with in-house and external training, coaching and language training.
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