Research Engineer- Neural Data (EEG)

Permanent contract
Paris
A few days at home
Salary: Not specified
Experience: > 3 years

Sigma Nova
Sigma Nova

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The position

Job description

We are finishing assembling our AI4Neuro team.

Having already recruited 3 Research Scientists, we are looking for the missing piece of the puzzle. Someone who will bring Best-in-class Software/ML engineering practices combined with deep EEG-data expertise.

This Research Engineer will have to design and maintain the infrastructure that makes our future brain foundation model research scalable, reproducible, and robust.

You’ll work at the intersection of neuroscience and AI, enabling fast iteration and transparent experimentation by building high-quality tooling, pipelines, and data systems.

More pragmatically, your mission will be to

  • Develop and maintain preprocessing pipelines for neural datasets (we are starting with EEG and have an ambition to expand to multimodality (fMRI/ECoG/MRI).

  • Build robust Python packages for data validation, visualisation, and reproducibility.

  • Manage versioning and traceability for datasets, models, experiments, and evaluation metrics

  • Collaborate closely with Research scientists and neuroscientists to co-design experiments.

  • Contribute to both internal tooling and open-source neuro- and ML-related codebases.


Preferred experience

  • Experience building neuroimaging pipelines (EEG)

  • Strong Python skills and experience building clean, well-tested packages

  • Familiarity with workflow/orchestration tools (e.g., DVC, Snakemake, Prefect, or custom systems)

  • Proficiency with PyTorch and deep learning workflows (e.g., training loops, evaluation, checkpointing)

  • A mindset focused on reproducibility, usability, and scientific clarity

Bonus points for:

  • Contributions to open-source projects in neuroimaging or ML (e.g., nilearn, Bids..)

  • Experience with brain atlas alignment, source localisation, or BIDS-compliant large-scale datasets

  • Interest in developing tools that serve both internal teams and the broader research community


Recruitment process

  • Application review (mid-August, after Paul’s holiday break)

  • Introductory call with Paul (Head of Talent Acquisition) – 30 min

  • Technical screen – 45 min with Richard (AI4Neuro team lead)

  • Behavioural interview with Paul – 45 min

  • A Half-day of technical interviews in our offices

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