# Founding MLOps - Data Platform Engineer at Noialabs > Hybrid · France · Unspecified · Backend · open. Source: https://alderhq.app/jobs/ashby%3Anoialabs%3A5b96d857-ea1c-4b2e-843b-92e91ec65c3d (read 2026-11-12). ## Facts (observed) - Company: [Noialabs](https://alderhq.app/companies/noialabs) - Location text: Paris HQ - Where it can be done from (inferred): Hybrid · France (evidence: "Location: Paris HQ") - Posted: 2026-06-08 (156 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-07 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/noialabs/5b96d857-ea1c-4b2e-843b-92e91ec65c3d - Skills listed (inferred): Python, Docker ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Paris, n 8): p25 €51k, median €59k, p75 €65k ## Description (the employer's text) ### 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 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. 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. ### What you’ll do Build and maintain the platform for neural data ingestion, processing, storage, and retrieval Develop pipelines for dataset generation, training, evaluation, and deployment Create tools that help ML engineers and scientists find data, run experiments, compare models, and reproduce results Manage cloud and GPU compute for scalable ML workloads Improve data quality, metadata, versioning, monitoring, and traceability Work with software and ML teams to integrate models into the platform Help define standards for reliability, reproducibility, privacy, and security ### What we are looking for 5+ years of experience building production-grade MLOps and data infrastructure Strong software engineering experience, especially in Python Experience with cloud infrastructure, containers, CI/CD, and production systems Experience supporting GPU workloads or distributed training Experience with ML tooling for training, evaluation, tracking, or deployment Strong understanding of data quality, monitoring, versioning, and reproducibility Strong ownership, practical problem-solving skills, and attention to detail ### Nice to have Experience with time-series data such as biosignals, sensor data, audio, video, or robotics Experience with real-time streaming, edge buffering, device-to-cloud synchronization, or intermittent connectivity Experience in health, medical device, regulated, privacy-sensitive, or research 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 - careers@noialabs.ai --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Anoialabs%3A5b96d857-ea1c-4b2e-843b-92e91ec65c3d and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.