About Dandelion Science

Dandelion Science is a Swiss-US Generative Neuromodulation™ company, advancing precision therapies for vision and brain disorders. Backed by NIH and Swiss Innovation Agency grants, and in partnership with the Wyss Center, our platform fuses generative AI with neuroscience to deliver real-time, patient-facing ML-driven therapeutics.

Position Overview

We’re looking for a hands-on engineer who writes production-grade Python every day, builds portable, modular code for scientific/ML workloads, and knows how to deploy and operate it at scale on AWS with Terraform. You’ll partner closely with our AI and research teams to turn notebooks into rock-solid services supporting real-time data processing in our neuromodulation platform.

Key Responsibilities

1. Core Python Development
   • Author clean, well-tested, modular Python libraries and services (pytest, sphinx, packaging)
   • Collaborate with data scientists to productionize numerical algorithms (NumPy, pandas, SciPy) and ML models (scikit-learn, PyTorch/TensorFlow)
2. Cloud & IaC
   • Design, deploy, and maintain AWS infrastructure (EC2, Lambda, S3, EKS, RDS)
   • Define all resources via Terraform (and Terragrunt) modules, enforce least-privilege IAM
   • Automate CI/CD for code and model pipelines using GitHub Actions/GitLab CI
3. MLOps & Real-Time Platform Support
   • Build model training, validation, and rollback workflows (model registry, feature store)
   • Instrument monitoring and logging (Prometheus/Grafana, ELK) to detect drift or performance degradation
   • Ensure low-latency, highly available operation for scientist and patient-facing services
4. Cross-Functional Collaboration
   • Work with neuroscience researchers and engineers in our US and Swiss teams
   • Document architecture, runbooks, and best practices to facilitate knowledge sharing

Qualifications

REQUIRED

• 4+ years production Python (pytest, packaging, modular design)
• Hands-on with scientific/ML libraries (NumPy, pandas, SciPy; scikit-learn, PyTorch/TensorFlow)
• AWS experience (compute, storage, networking) and IaC (e.g., Terraform) practitioner Nice-to-Have
• MLOps experience: CI/CD, containerization (Docker/K8s/EKS), model monitoring
• Healthcare/neuroscience domain experience (GDPR, HIPAA familiarity)
• Real-time data streaming (Lab Streaming Layer)
• Feature-store tools (e.g., Feast) or server frameworks (TorchServe, TF-Serving)

Why You’ll Love It Here

• High Impact: Drive real-time AI therapies at the cutting edge of neuroscience
• Collaborative Team: Partner with world-class researchers and engineers
• Growth & Equity: Competitive equity package, plus NIH & Innosuisse backing
• Swiss-US Culture: Hybrid environment with Geneva HQ and U.S. research labs