Data Platform Engineer at LeibnizRechenzentrum LRZ der Bayerischen Akademie der Wissenschaften

Berlin, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

21 Dec, 26

Salary

80000.0

Posted On

22 Sep, 26

Experience

8 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Information Technology & Services

Description

Your Role and Responsibilities:

Developing and maintaining the data facility of the AI Factory including its software environments in the context of AI, HPC and data analytics use cases for modern AI, high-performance and cloud computing systems
Contributing to the initial (and evolving) service portfolio of the AI Factory within a friendly and open work environment in a highly motivated, international team with opportunities to contribute with your own ideas
Supporting and enabling customers to publish, access and share their own AI data sets and models
Fostering contact with collaboration partners as well as stakeholders from the European AI ecosystem, relying on your friendly personality and communication skills
Opportunities to work with national and European partners on novel AI R&D projects from the private and academic sectors
Maintaining relationships with technology providers and system developers (software/hardware)

Your Qualifications:

Required/Minimum Qualifications

PhD or Master’s degree in computer or data science, or other areas of scientific computing, or a Bachelor’s degree with multiple years (>3) of applied data platform development / engineering / deployment experience and/or working with AI data management workflows ideally as senior engineer in research or enterprise environments

Other Requirements

Proficiency working in data center environments (incl. Linux, Git, Gitlab)
Willingness to keep up with current developments and to learn new technologies in the field of AI
Extensive knowledge and experience in developing and working with data platforms including their backend components in the context of AI, HPC and data analytics use cases (preferably piveau, www.piveau.de)
Extensive knowledge about and practical skills in specifying and implementing FAIR-aligned (Findable, Accessible, Interoperable, Reusable) data management workflows
Knowledge and experience in developing integration layers for connecting data infrastructure with external data platforms, preferably through metadata standards
Knowledge about and practical skills in secure and compliant data management, including AI models as well as data privacy standards and legislation
Excellent English and preferably German presentation and writing skills

Additional and Preferred Qualifications

Knowledge and experience with dataspaces, ideally within the Common European Data Space initiative
Knowledge and experience in software deployment and software lifecycle management (ideally based on principles of continuous integration/continuous deployment, CI/CD)
Basic knowledge and practical skills in software design and engineering
Basic knowledge and practical skills in IT and cybersecurity for software and software platform development
Experience with agile development methods

How To Apply:

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Responsibilities

Developing and maintaining the data facility of the AI Factory including its software environments in the context of AI, HPC and data analytics use cases for modern AI, high-performance and cloud computing systems
Contributing to the initial (and evolving) service portfolio of the AI Factory within a friendly and open work environment in a highly motivated, international team with opportunities to contribute with your own ideas
Supporting and enabling customers to publish, access and share their own AI data sets and models
Fostering contact with collaboration partners as well as stakeholders from the European AI ecosystem, relying on your friendly personality and communication skills
Opportunities to work with national and European partners on novel AI R&D projects from the private and academic sectors
Maintaining relationships with technology providers and system developers (software/hardware)

Required/Minimum Qualifications

PhD or Master’s degree in computer or data science, or other areas of scientific computing, or a Bachelor’s degree with multiple years (>3) of applied data platform development / engineering / deployment experience and/or working with AI data management workflows ideally as senior engineer in research or enterprise environments

Other Requirements

Proficiency working in data center environments (incl. Linux, Git, Gitlab)
Willingness to keep up with current developments and to learn new technologies in the field of AI
Extensive knowledge and experience in developing and working with data platforms including their backend components in the context of AI, HPC and data analytics use cases (preferably piveau, www.piveau.de)
Extensive knowledge about and practical skills in specifying and implementing FAIR-aligned (Findable, Accessible, Interoperable, Reusable) data management workflows
Knowledge and experience in developing integration layers for connecting data infrastructure with external data platforms, preferably through metadata standards
Knowledge about and practical skills in secure and compliant data management, including AI models as well as data privacy standards and legislation
Excellent English and preferably German presentation and writing skills

Additional and Preferred Qualifications

Knowledge and experience with dataspaces, ideally within the Common European Data Space initiative
Knowledge and experience in software deployment and software lifecycle management (ideally based on principles of continuous integration/continuous deployment, CI/CD)
Basic knowledge and practical skills in software design and engineering
Basic knowledge and practical skills in IT and cybersecurity for software and software platform development
Experience with agile development methods