Research Software Engineer – AI and Earth Observation

Job description

Zur Jobsuche Startseite Stellenangebot: Research Software Engineer – AI and Earth Observation bei Forschungszentrum Jülich GmbH P-VA Personalabrechnung Das Wichtigste im Überblick Besondere Merkmale Arbeitsort Jülich Angebotsart Arbeit Anstellungsart Vollzeit Beginn ab sofort Berufsbezeichnung Data Engineer Info zur Bewerbung Vormerken Notiz / Status Notiz hinzufügen Bitte anmelden, um diese Funktion zu nutzen. Bewerbungsstatus hinzufügen Bitte anmelden, um diese Funktion zu nutzen. PDF / Drucken Teilen Veröffentlichungsdatum: Vor 23 Tagen veröffentlicht Änderungsdatum: Vor 17 Tagen bearbeitet Stellenbeschreibung Research Software Engineer – AI and Earth Observation The operates one of the most powerful computer systems for scientific and technical applications in Europe and makes it available to scientists at Forschungszentrum Jülich, in Germany and across Europe for research purposes via an independent peer-review process. As part of this remit, the JSC carries out research and development work in the fields of technology, HPC systems, communications, highly scalable data science, mathematics and application support. The department develops machine learning techniques and other methods and tools for the management, analysis and modelling of large-scale data, and for the integration of data and computing resources into federated HPC infrastructures. The models, tools and methods are developed in collaboration with users in selected scientific domains, tested, scaled for the pre-zettascale era and offered as generic solutions to a large number of scientific communities. Join us now and contribute with your expertise to this interesting field. Your Job In this position, you will join our . The lab advances interdisciplinary research and operational services by combining geoscience and remote sensing methods with AI and advanced computing technologies for Earth observation (EO) applications. Your work will focus on deploying, operating and scaling scientific software, AI services and data workflows across supercomputing, cloud and quantum computing environments. You will work closely with our researchers and international partners from academia, industry and public agencies, bringing together scientific computing, data engineering and AI to address EO challenges. Specifically, you will: Design, deploy and operate end-to-end federated EO and AI workflows, from multisource data collection and pre-processing to model training, serving and delivery of actionable information Build and maintain containerised and cluster-based environments for AI services, including deployment pipelines, monitoring, logging and alerting Develop, port and optimise scientific software and workflows across HPC, cloud and hybrid quantum-classical environments, ensuring performance, scalability, portability and reliability Apply sustainable software engineering and MLOps practices, including CI/CD, automated testing, packaging, versioning and documentation, to support reproducibility and maintainability Develop and document stable APIs and accessible interfaces that help users integrate EO and AI services into their operational workflows Collaborate with researchers and infrastructure teams to align applications with available computing, storage and networking resources, and support the adoption of HPC and AI services Contribute expertise in advanced analytics to research initiatives and the preparation of proposals for national and international funding calls and tenders Contribute to open-source projects, technical reports, publications, presentations and educational activities, including courses, hackathons and community events Your Profile Your qualifications and technical background include: An excellent master’s degree in computer science, software engineering, data science or a related field. A subsequent PhD is not required but would be a plus At least a few years of industry experience in software engineering, data engineering, scientific computing or AI engineering, with hands-on experience delivering and supporting production software, data-intensive workflows or computing services Strong programming skills and practical experience with Linux, containerisation, version control and service deployment on HPC systems or cloud infrastructure, including GPU-accelerated workloads Experience with deep learning frameworks, production model serving and end-to-end data and model pipelines, including monitoring, experiment tracking and model lifecycle management Evidence of research or software contributions through publications and/or open-source projects Self-motivation, autonomy and sound judgement, with the ability to take a system-wide view and adapt to operational challenges The ability to collaborate effectively in multidisciplinary, international teams, supported by a very good command of written and spoken English with extensive vocabulary (at least B2 level according to the ), ideally supported by a certificate confirming the l