Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces.
We're tackling one of the most ambitious problems in human-AI interaction: decoding human intent directly from brain signals, in real time and without surgery, to control and collaborate with AI systems.
Our approach combines optimized neural sensors with large-scale AI models trained across many users, a technical challenge that sits at the intersection of neurotechnologies and frontier AI.
Founded by the team behind NextMind (acquired by Snap) and backed by tier-1 investors, Noïa Labs is starting its journey and hiring a team of outstanding engineers and scientists where each person will have a major impact on the product and technology.
We are seeking a talented Machine Learning Scientist to develop the modeling approaches behind our non-invasive neural interface. You will work on learning from neural and multimodal time-series data to help infer human intent and enable new forms of interaction with AI systems.
This is a hands-on research role for someone who enjoys developing new ML methods, running rigorous experiments, and turning promising ideas into working prototypes. The role spans representation and self-supervised learning, neural decoding, model evaluation, personalization, and real-time adaptation, in close collaboration with BCI scientists, ML engineers, and product teams.
Develop new ML methods for neural and multimodal time-series data
Design rigorous experiments, benchmarks, and ablations to evaluate model performance and generalization
Translate research ideas into prototypes tested on real data and in user studies
Collaborate with BCI scientists and ML engineers to turn neuroscience-informed modeling ideas into reliable training and inference workflows.
5+ years of experience in machine learning research, applied ML research, or a related field
PhD, MS, or equivalent research experience in machine learning, computer science, computational neuroscience, applied mathematics, physics, electrical engineering, or a related field
Strong experience with deep learning for time-series, sequential, multimodal, or sensor data
Strong experience with PyTorch, JAX, TensorFlow, or similar frameworks
Strong understanding of representation learning, self-supervised learning, transformers, generative models, or foundation models
Experience designing rigorous ML experiments, benchmarks, ablations, and evaluation protocols
Experience with neural or physiological time-series such as EEG, MEG, ECoG, EMG, eye tracking, PPG, or audio
Experience with online learning, personalization, calibration, domain adaptation, or transfer learning
Experience with real-time inference, edge deployment, or low-latency ML systems
Publications or strong research output in machine learning, computational neuroscience, signal processing, or related fields
Experience working in a fast-moving startup or research-to-product environment
Equity package
Full health coverage, employer-paid through Alan
100% reimbursement of public transport costs (Paris-based)
Meal vouchers at €11 per working day, 60% company-funded
New MacBook Pro
RTT (extra days off)
Even if you don't check every box in our requirements, we encourage you to apply. We value diverse perspectives and backgrounds, and we're more interested in your potential and passion than a perfect match to our checklist.
In case of any doubts or questions, please contact - [email protected]
