Founding ML Scientist — Real-Time Brain-Interface AI

Noïa Labs; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Equity package

Full health coverage

Public transport reimbursement (Paris)

Meal vouchers

New MacBook Pro

RTT (extra days off)

Résumé du poste

Noïa Labs is building non-invasive brain-computer interfaces to decode human intent in real time. As a Machine Learning Scientist, you will develop modeling approaches for neural and multimodal data, conduct rigorous experiments, and turn ideas into working prototypes in collaboration with BCI scientists, ML engineers, and product teams.

You will explore representation learning, self-supervised learning, and real-time adaptation, contributing to end-to-end training and deployment while advancing

Qualifications

• 5+ years of experience in machine learning research or related field.
• PhD, MS, or equivalent research experience in ML/CS/related field.
• Strong experience with time-series, sequential, multimodal, or sensor data.
• Proficient in PyTorch, JAX, TensorFlow or similar frameworks.
• Knowledge of representation learning, self-supervised learning, transformers, or foundation models.

Responsabilités

• Develop new ML methods for neural and multimodal time-series data.
• Design rigorous experiments, benchmarks, and ablations to evaluate model performance.
• Translate research ideas into prototypes tested on real data and user studies.
• Collaborate with BCI scientists and ML engineers to deploy training and inference workflows.

Connaissances

Time-series ML

Deep learning

PyTorch/TensorFlow/JAX

Representation learning

Experiment design

Formation

PhD or MS in ML/CS/related field

Outils

PyTorch

JAX

TensorFlow

Description du poste

Noïa Labs is building non-invasive brain-computer interfaces to decode human intent in real time. As a Machine Learning Scientist, you will develop modeling approaches for neural and multimodal data, conduct rigorous experiments, and turn ideas into working prototypes in collaboration with BCI scientists, ML engineers, and product teams.

You will explore representation learning, self-supervised learning, and real-time adaptation, contributing to end-to-end training and deployment while advancing