
Sigma Nova builds large-scale AI foundations to accelerate scientific breakthroughs. It develops foundation models and Gen AI capabilities through partnerships that unlock diverse datasets from…

Sigma Nova builds large-scale AI foundations to accelerate scientific breakthroughs. It develops foundation models and Gen AI capabilities through partnerships that unlock diverse datasets from…
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We’re building foundational models for scientific signals, starting with the brain (EEG, fMRI, ultrasound), and we aim to extend these approaches to other complex domains.
We work with temporal signals, collected under real-world constraints (e.g., clinical settings with limited sample sizes): our data is noisy and heterogeneous.
As the architect of our “Data & Training Factory,” you’ll:
Scale Pre-training to New Frontiers
Finetune pretrained models on both open-source and proprietary data
Engineer Multimodal Data Pipelines
Uphold Scientific Rigor & Software Standards
3–7 years of experience in applied research or R&D.
Distributed Training: Proven track record with large-scale model training.
PyTorch Mastery: Deep knowledge of internals (memory, kernels, attention mechanisms).
Data Engineering: Robust pipelines, versioning, and data quality.
Scientific Rigor: Experience in research environments with high software standards.
While technical excellence is critical, we place equal importance on how we work together. We believe the best teams are built on:
Integrity & Respect
Open Communication & Humility
Psychological Safety & Camaraderie
Technical Screen with one Research Scientist or Research Engineer
On-site (Take-home exercise and restitution + Behavioural interview)