Role Summary
We re looking for a hands-on AI & Data Platform Architect to design and build a scalable secure and modular platform that powers AI research in healthcare. You ll lead the technical architecture for training and deploying models on complex biomedical data helping shape the future of AI in life sciences.
Key Responsibilities
- Design and build a scalable AI/ML platform to support data pipelines model training and deployment.
- Work with large diverse biomedical datasets (clinical genomic proteomic chemical).
- Build secure cloud-native infrastructure using containers and APIs.
- Implement and scale foundation models knowledge graphs and embeddings.
- Ensure compliance with security and privacy standards (e.g. HIPAA SOC2).
- Collaborate with cross-functional teams (data scientists clinicians engineers).
- Mentor engineers and set best practices for ML platforms and MLOps.
Required Skills & Experience
- Master s or PhD in Computer Science AI/ML or related field.
- 10 years in AI platform or infrastructure roles.
- Strong experience with Python ML frameworks (PyTorch TensorFlow) and cloud platforms (AWS GCP Azure).
- Experience with distributed systems MLOps and tools like MLFlow Kubeflow Databricks.
- Familiar with GPUs performance optimization and data security practices.
Nice to Have
- Background in life sciences or biomedical data (genomics proteomics EHRs).
- Familiarity with drug discovery workflows and generative AI tools like LangChain or Hugging Face.
- Knowledge of bioinformatics databases and ontologies.
What We Offer
- Chance to shape a cutting-edge AI platform in a mission-driven startup.
- Equity and growth opportunities in a fast-moving team.
- Budget for learning and experimentation with AI/cloud tools.