Machine Learning Engineer (Re1-2) - Ai Factory (Earth Sciences Department)
Role details
Job location
Tech stack
Job description
Context and Mission: The Barcelona Supercomputing Center (BSC) is seeking a Machine Learning Engineer to join the Earth Sciences department within the AI Factory initiative. The AI Factory accelerates adoption and development of AI across industry sectors, deploying AI-focused services including training, networking, and innovation support. The MareNostrum5 AI partition provides the computing backbone for these services. The selected candidate will support AI services related to climate change use cases, coordinate availability and integration of AI software on MareNostrum5, and ensure smooth support for the AI Factory user community. Responsibilities
- Support the documentation and curation of AI software employed in the AI Factory
- Support the deployment and maintenance of AI software on the MareNostrum5 AI partition
- Design, implement, and optimize machine learning pipelines for environmental-related applications
- Collaborate with domain scientists and external users to develop AI solutions
- Support users from the AI Factory in accessing and utilizing AI tools and services
- Participate in collaborative development within the AI Factory consortium
- Participate in technical reporting and scientific publications contributing to the documentation of the AI Factory software, with opportunities to be involved in academic publications and project reporting
Requirements
Bachelor's or Master's in Computer Science, Machine Learning, Data Science, Environmental Sciences, or a related field. Essential Knowledge And Professional Experience
- Strong programming skills in Python, with experience in machine learning libraries such as PyTorch, TensorFlow, and Scikit-learn
- Proven experience in developing and training machine learning models, particularly deep learning architectures
- Strong background in handling, analyzing, and validating large-scale datasets
- Experience working in a UNIX-based computational environment
Additional Knowledge And Professional Experience
- Familiarity with climate, weather, and Earth system datasets (NetCDF, Zarr)
- Experience in high-performance computing (HPC) and parallelized machine learning workflows
- Proficiency in GPU-accelerated machine learning frameworks such as TensorFlow, RAPIDS, JAX, and/or distributed training using Dask
- Understanding of climate and weather models
Competences
- Strong problem-solving and analytical skills, with the ability to optimize computational workflows
- Ability to work independently while collaborating effectively in a research environment
- Excellent communication skills, with a strong ability to document and present research findings
- Proficiency in written and spoken English, * A full CV in English including contact details
- A cover/motivation letter with a statement of interest in English, clearly specifying the area and topics of interest; two references for further contact must be included
Benefits & conditions
We offer a full-time contract (37.5h/week), a good working environment, state-of-the-art infrastructure, flexible working hours, extensive training plan, restaurant tickets, private health insurance, and support for relocation procedures.
Duration: Open-ended contract due to project and budget considerations.
Holidays: 22 days of holidays + 6 personal days + 24th and 31st of December.
Salary: Competitive salary commensurate with qualifications and experience, aligned with Barcelona cost of living.
