Research Engineer Intern: Efficient ML for Brain Signals

Sigma Nova; Paris; On-site; EUR 11,000 - 17,000; Full time

Benefits offered by this job

Mentorship

GPU access

Publication opportunities

Job summary

Sigma Nova in Paris is offering an internship (March–April 2027) to work with researchers on training and deploying models for neural time series, focusing on something measurable—a benchmark, a reusable tool, or a working prototype.

You'll explore efficient models, scalable brain-signal processing, and reliable experimentation, with close mentorship, GPU access, and opportunities to contribute to a publication depending on project results.

Qualifications

• Strong Python skills with PyTorch experience.
• Solid deep learning fundamentals and interest in efficient ML systems.
• Enjoy writing clean code, debugging, and measuring what actually improves.

Responsibilities

• Work with researchers on training and deploying models for neural time series.
• Contribute to a benchmark, reusable tool, or working prototype.
• Develop and evaluate efficient models and scalable data processing pipelines.

Skills

Python

PyTorch

Deep learning

Code quality

Job description

Sigma Nova in Paris is offering an internship (March–April 2027) to work with researchers on training and deploying models for neural time series, focusing on something measurable—a benchmark, a reusable tool, or a working prototype.

You'll explore efficient models, scalable brain-signal processing, and reliable experimentation, with close mentorship, GPU access, and opportunities to contribute to a publication depending on project results.