Machine Learning Engineer (d/f/m)

Webseite Airbus

Antrittsdatum: Nach Vereinbarung

Job Description:

We are searching for a Machine Learning Engineer (d/f/m) for the Defence and Space central data analytics & AI deployment team (within DTO), who can support the industrialisation of data analytics applications.  This position will have a special focus on MLOps, whose primary responsibility will be contributing to the development and deployment of MLOps tools to ensure the reliable operation of machine learning models in production.

The goal of MLOps is to deploy and maintain machine learning models reliably and efficiently at scale across an organization. To support data scientists from data collection to model training and making the model available for the end users a wide range of skills are needed from Machine Learning and Data Engineering, to Cloud and DevOps.

Tasks and accountability

  • Extending and improving the data science infrastructure at Airbus DS
  • Creating and maintaining highly performant and scalable ML services
  • Developing tools to enable Data Scientists and enhance their productivity
  • Bridging the gap between research and production
  • Working with domain experts and Data Scientists to accelerate ML into production
  • Developing MLOps solutions, tools, practices and culture
  • Contributing to architecture design, development of data or machine learning pipelines, and integration into enterprise systems

Required Skills

Ideally you will have a Master Degree in Computer science, computer engineering, IT or a related discipline and at least 2-3 years relevant technical experience across the technologies listed,  and that you are able to demonstrate the application of your experience against these technologies from previous projects/employers.  In addition certification or professional qualifications in appropriate technologies would be an advantage.

You have the experience and the following skills:

  • distributed data processing technologies (Spark, Flink, Beam, etc.)
  • Hadoop ecosystem and its distributions (Cloudera, HDP, etc.)
  • streaming platforms/message brokers (Kafka, RabbitMQ, Amazon Kinesis, etc.)
  • NoSQL databases (MongoDB, DynamoDB, Neo4j, Druid, etc.)
  • pipeline tools (Airflow, Prefect, etc.)
  • MLOps tools (Kubeflow, MLflow, TFX, Sagemaker, Seldon, etc.)
  • logging and monitoring (EFK stack, Prometheus, Grafana, etc.)
  • data versioning (DVC, Pachyderm, etc.)
  • cloud infrastructure (preferably AWS)
  • ML frameworks (Tensorflow, PyTorch, sklearn, etc.) and a good understanding of the full ML lifecycle
  • CI/CD pipelines and DevOps
  • application containerization and orchestration tools like Docker, Kubernetes and Helm
  • software development, ideally with Python, preferably in a machine learning related role

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Airbus Defence and Space GmbH

Contract Type:
Permanent Contract / CDI / Unbefristet / Contrato indefinido

Experience Level:
Professional / Expérimenté(e) / Professionell / Profesional

Job Family:
Information Mgmt and Digital Technology

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

Tagged as: Airbus, Machine Learning, Plus

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