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Founding MLOps - Data Platform Engineer

Noïa Labs
Paris (75)

Postuler rapidement

Détails de l'emploi

Temps plein

Avantages

Qualifications

CI/CD
Infrastructure cloud
Production
Python

Description complète du poste

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 - [email protected]

Postuler rapidement

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