**About Dandelion Science**

Dandelion Science is a Swiss-US NeuroAI company advancing precision therapies for vision and brain disorders. Backed by NIH, Innosuisse, and a multi-year collaboration with the Wyss Center, we build AI-driven neurotechnology that directly interfaces with human neural activity.

**Position Overview**

A
*NeuroAI Research Engineer*

at Dandelion designs, implements, and deploys machine learning systems that interact with neural signals. This is a hybrid research + engineering role: you will create and prototype new cutting-edge models, and  also write robust, scalable, production-grade code. You will work across modalities (video, neuroimaging, behavior) and across the full lifecycle, from model research to training infrastructure to deployment.

This role is ideal for someone who loves pushing the frontiers of NeuroAI by combining deep learning with neuroscience; and identifies equally as a strong software engineer who cares about performance, clarity, reproducibility, and collaborative development.

**Key Responsibilities****Model Design & Engineering**

- Develop and optimize advanced ML models (generative models, video world models, sequence models) for neuroimaging data (EEG, MEG, fMRI).
- Write clean, efficient, testable code in Python; design components that scale across GPUs and multi-node clusters.
- Debug complex system-level issues (timing, memory, threading, distributed training).

**Pipelines & Infrastructure**

- Build and maintain scalable ETL, training, and evaluation pipelines (cloud-native on AWS/GCP).
- Contribute to model-serving frameworks and MLOps workflows (versioning, CI/CD, reproducibility, monitoring).
- Ensure experiments are reproducible via structured configs, logging, and artifact storage.

**Collaboration & Translation**

- Work closely with neuroscience, clinical, ML and software teams to turn prototypes into reliable components.
- Write technical documentation and communicate engineering constraints and research results clearly.

**Qualifications****Required**

- Ph.D. or Master’s in Computer Science, Computational Neuroscience, Electrical Engineering, Applied Math, or related field.
- 2+ years experience in an applied research engineering role or close collaboration with industry R&D teams.
- Strong deep learning experience (e.g., generative models, computer vision, sequence models).
- Demonstrated ability to develop and ship production-quality software in large collaborative codebases.
- Strong Python engineering skills (PyTorch required).
- Experience with cloud platforms (AWS/GCP/Azure), containers, and distributed training.
- Solid grounding in software engineering practices:
- Git/GitHub workflows
- testing frameworks
- CI/CD
- type checking / linting
- reproducible environments (conda, Docker)
- Excellent communication and documentation abilities.

**Preferred**

- Experience optimizing models for speed, memory, and multi-GPU performance.
- Experience with real-time video processing or low-latency streaming systems.
- Familiarity with EEG/MEG/fMRI preprocessing or time-series signal processing.
- Knowledge of Bayesian optimization or reinforcement learning for real-time adaptive systems.

**Why Join Dandelion Science?**

- Work on foundational NeuroAI technology with direct impact on real patients.
- Collaborate with leading teams across neuroscience, AI, clinical research, and product development.
- Push the frontiers of digital twins for the human brain with cutting-edge compute and experimental infrastructure.
- Equity participation and meaningful ownership in a rapidly growing company.
- Join a highly interdisciplinary, ambitious team pushing the boundaries of generative neuromodulation.

**Application Process**

Please submit your CV, a cover letter, and any relevant publications or code samples to
careers@dandelion.science.

Dandelion Science is an equal-opportunity employer committed to diversity and inclusion.