Noïa Labs

<h2><strong>About Noïa Labs</strong></h2><div> </div><p>Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces.</p><p>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.</p><p>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.</p><p>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.</p><p></p><h2><strong>Your Mission</strong></h2><p>We are seeking a talented MLOps / Data Platform Engineer to build the data and ML infrastructure behind our non-invasive neural interface. You will own the systems that ingest, version, and serve large-scale neural data, making model training fast, reproducible, and scalable from dataset construction and orchestration through distributed training and deployment.</p><p>This is a hands-on role for someone who enjoys building reliable infrastructure for fast-moving ML and research teams. The role spans data pipelines, ML workflows, compute infrastructure, experiment tracking, model deployment, and internal tooling, while working closely with ML engineers, neuroscientists, software engineers, and product teams.</p><p></p><h2><strong>What you’ll do:</strong></h2><ul><li><p>Build and maintain the platform for neural data ingestion, processing, storage, and retrieval</p></li><li><p>Develop pipelines for dataset generation, training, evaluation, and deployment</p></li><li><p>Create tools that help ML engineers and scientists find data, run experiments, compare models, and reproduce results</p></li><li><p>Manage cloud and GPU compute for scalable ML workloads</p></li><li><p>Improve data quality, metadata, versioning, monitoring, and traceability</p></li><li><p>Work with software and ML teams to integrate models into the platform</p></li><li><p>Help define standards for reliability, reproducibility, privacy, and security</p><p></p></li></ul><h2><strong>What we are looking for:</strong></h2><ul><li><p>5+ years of experience building production-grade MLOps and data infrastructure</p></li><li><p>Strong software engineering experience, especially in Python</p></li><li><p>Experience with cloud infrastructure, containers, CI/CD, and production systems</p></li><li><p>Experience supporting GPU workloads or distributed training</p></li><li><p>Experience with ML tooling for training, evaluation, tracking, or deployment</p></li><li><p>Strong understanding of data quality, monitoring, versioning, and reproducibility</p></li><li><p>Strong ownership, practical problem-solving skills, and attention to detail</p><div> </div></li></ul><h2><strong>Nice to have:</strong></h2><ul><li><p>Experience with time-series data such as biosignals, sensor data, audio, video, or robotics</p></li><li><p>Experience with real-time streaming, edge buffering, device-to-cloud synchronization, or intermittent connectivity</p></li><li><p>Experience in health, medical device, regulated, privacy-sensitive, or research environments</p></li></ul><p></p><h2><strong>Benefits &amp; Compensation:</strong></h2><ul><li><p>Equity package</p></li><li><p>Full health coverage, employer-paid through Alan</p></li><li><p>100% reimbursement of public transport costs (Paris-based)</p></li><li><p>Meal vouchers at €11 per working day, 60% company-funded</p></li><li><p>New MacBook Pro</p></li><li><p>RTT (extra days off)</p><div> </div></li></ul><p><em>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.</em></p><p></p><p>In case of any doubts or questions, please contact - <u>careers@noialabs.ai</u></p><p></p><p></p>

Founding MLOps - Data Platform Engineer

<h2><strong>About Noïa Labs</strong></h2><div> </div><p>Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces.</p><p>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.</p><p>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.</p><p>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.</p><p></p><h2><strong>Your Mission</strong></h2><p>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.</p><p>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.</p><p></p><h2><strong>What you’ll do:</strong></h2><ul><li><p>Develop new ML methods  for neural and multimodal time-series data</p></li><li><p>Design rigorous experiments, benchmarks, and ablations to evaluate model performance and generalization</p></li><li><p>Translate research ideas into prototypes tested on real data and in user studies</p></li><li><p>Collaborate with BCI scientists and ML engineers to turn neuroscience-informed modeling ideas into reliable training and inference workflows.</p><p><br /></p></li></ul><h2><strong>What we are looking for:</strong></h2><ul><li><p>5+ years of experience in machine learning research, applied ML research, or a related field</p></li><li><p>PhD, MS, or equivalent research experience in machine learning, computer science, computational neuroscience, applied mathematics, physics, electrical engineering, or a related field</p></li><li><p>Strong experience with deep learning for time-series, sequential, multimodal, or sensor data</p></li><li><p>Strong experience with PyTorch, JAX, TensorFlow, or similar frameworks</p></li><li><p>Strong understanding of representation learning, self-supervised learning, transformers, generative models, or foundation models</p></li><li><p>Experience designing rigorous ML experiments, benchmarks, ablations, and evaluation protocols </p></li></ul><p></p><h2><strong>Nice to have:</strong></h2><ul><li><p>Experience with neural or physiological time-series such as EEG, MEG, ECoG, EMG, eye tracking, PPG, or audio</p></li><li><p>Experience with online learning, personalization, calibration, domain adaptation, or transfer learning</p></li><li><p>Experience with real-time inference, edge deployment, or low-latency ML systems</p></li><li><p>Publications or strong research output in machine learning, computational neuroscience, signal processing, or related fields</p></li><li><p>Experience working in a fast-moving startup or research-to-product environment</p><p></p></li></ul><h2></h2><h2><strong>Benefits &amp; Compensation:</strong></h2><ul><li><p>Equity package</p></li><li><p>Full health coverage, employer-paid through Alan</p></li><li><p>100% reimbursement of public transport costs (Paris-based)</p></li><li><p>Meal vouchers at €11 per working day, 60% company-funded</p></li><li><p>New MacBook Pro</p></li><li><p>RTT (extra days off)</p><div> </div></li></ul><p><em>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.</em></p><div> </div><p>In case of any doubts or questions, please contact - <u>careers@noialabs.ai</u><br /></p>

Founding Machine Learning Scientist

<h2><strong>About Noïa Labs</strong></h2><div> </div><p>Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces. </p><p>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. </p><p>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.</p><p>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.</p><p></p><h2><strong>Your Mission</strong></h2><p>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.</p><p>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.</p><p></p><h2><strong>What you’ll do:</strong></h2><ul><li><p>Build and maintain scalable ML pipelines for training, inference, and evaluation</p></li><li><p>Train, evaluate, and deploy models on large-scale neural time-series data.</p></li><li><p>Develop tooling to evaluate model quality across users, sessions, and tasks</p></li><li><p>Optimize models for robustness, latency, and real-time use</p></li><li><p>Contribute to data processing, benchmarking, and automated evaluation workflows</p></li><li><p>Collaborate with researchers to turn new modeling approaches into production</p><p></p></li></ul><h2><strong>What we are looking for:</strong></h2><ul><li><p>Strong experience with modern ML frameworks (PyTorch, JAX or TensorFlow)</p></li><li><p>Strong experience with SSL, transformers, or foundation-model training</p></li><li><p>Strong experience with time-series (sensor data, audio, finance, robotics, etc)</p></li><li><p>Experience building reproducible training and evaluation pipelines.</p></li><li><p>Experience building and deploying production-grade ML systems</p></li><li><p>Familiarity with cloud infrastructure, GPUs, and scalable compute environments</p></li></ul><p></p><h2><strong>Benefits &amp; Compensation:</strong></h2><ul><li><p>Equity package</p></li><li><p>Full health coverage, employer-paid through Alan</p></li><li><p>100% reimbursement of public transport costs (Paris-based)</p></li><li><p>Meal vouchers at €11 per working day, 60% company-funded</p></li><li><p>New MacBook Pro</p></li><li><p>RTT (extra days off)</p><div> </div></li></ul><p><em>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.</em></p><p></p><p>In case of any doubts or questions, please contact - <u>careers@noialabs.ai</u></p>

Noïa Labs

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Founding MLOps - Data Platform Engineer

Founding Machine Learning Scientist

Founding Machine Learning Engineer

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