Founding Machine Learning Engineer

About Noïa Labs 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. Your Mission We are seeking a talented Machine Learning Engineer to build the models and ML systems behind our neural interface platform. You will play a pivotal role in designing, training, evaluating, and deploying models that learn from neural time-series data. The role spans model development, data pipelines, evaluation tooling, optimization, and deployment. You will work closely with BCI researchers and product engineers to build systems that are accurate, scalable, and usable in real time. This is a hands-on role for someone who can build reliable ML systems and moves fluidly between research and production. What you’ll do: Build and maintain scalable ML pipelines for training, inference, and evaluation Train, evaluate, and deploy models on large-scale neural time-series data. Develop tooling to evaluate model quality across users, sessions, and tasks Optimize models for robustness, latency, and real-time use Contribute to data processing, benchmarking, and automated evaluation workflows Collaborate with researchers to turn new modeling approaches into production What we are looking for: Strong experience with modern ML frameworks (PyTorch, JAX or TensorFlow) Strong experience with SSL, transformers, or foundation-model training Strong experience with time-series (sensor data, audio, finance, robotics, etc) Experience building reproducible training and evaluation pipelines. Experience building and deploying production-grade ML systems Familiarity with cloud infrastructure, GPUs, and scalable compute environments Benefits & Compensation: 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]