About ELDA

At ELDA, we’re building intelligent medical systems to accelerate the understanding and treatment of neurological disorders. Our interdisciplinary team combines neuroscience, data science, and engineering expertise to create cutting-edge biomedical solutions.

About the Role

We are seeking a junior to mid-level Python Engineer with hands-on experience in production environments. You thrive on solving complex technical challenges and are passionate about developing robust, data-driven systems.

In this role, you will:

• Design and implement a modular analysis pipeline with multiple scalable processing stages.
• Manage and maintain physiological signal data processing, configuration management, logging, and data integrity.
• Support ELDA’s data infrastructure and storage systems, integrating your pipeline with other solution components such as data acquisition platforms and visualization tools.
• Collaborate closely with neuroscientists, data scientists, and engineers to deliver impactful solutions in the biomedical domain.

Required Qualifications

• Minimum 1 year of industry experience working on production Python projects.
• Strong proficiency in Python, including OOP and debugging.
• Experience with Git and version control workflows.
• Familiarity with Docker for reproducible environments.
• Testing frameworks: pytest or equivalent.
• Proficiency with data analysis libraries: NumPy, SciPy, Pandas.
• Comfort with Linux command-line tools.
• Experience using AI-assisted coding tools (e.g., Cursor, Copilot).
• Ability to write clean, modular, and well-documented code.
• Comfortable reading and implementing technical documentation, research papers, and data specifications.
• Strong communication and self-management skills in an asynchronous team environment.

Helpful Experience

• Familiarity with signal processing techniques (filtering, resampling, artifact detection, segmentation).
• Experience working with physiological or biosignal data (EEG, ECG, EMG, etc.).
• Knowledge of environment management tools (Poetry, venv).
• Exposure to CI/CD workflows (GitHub Actions, GitLab CI).
• Understanding of parallelization frameworks and scalable data pipelines.

Please contact [email protected] and refer to position 347 in the title