Founding ML Engineer, Real-Time Brain Interfaces

Noïa Labs; Paris; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Equity package

Health coverage (Alan)

Public transport reimbursement (Paris)

Meal vouchers (€11)

MacBook Pro

RTT (extra days off)

Job summary

Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces. We are seeking a talented Machine Learning Engineer to design, train, evaluate, and deploy models that learn from neural time-series data in real time.

You will build scalable ML pipelines, work with BCI researchers and product engineers, and drive production-ready systems with robust tooling and scalable compute environments.

Qualifications

• Experience with modern ML frameworks (PyTorch, JAX or TensorFlow).
• Experience with SSL, transformers, or foundation-model training.
• 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.

Responsibilities

• 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.

Skills

ML frameworks

Transformer models

Time-series data

Reproducible pipelines

Production ML systems

Cloud/GPU infra

Job description

Noïa Labs is an early-stage neurotechnology company building the next generation of human-AI interfaces. We are seeking a talented Machine Learning Engineer to design, train, evaluate, and deploy models that learn from neural time-series data in real time.

You will build scalable ML pipelines, work with BCI researchers and product engineers, and drive production-ready systems with robust tooling and scalable compute environments.