Principal AI Scientist

Principal AI Scientist

Role Overview
We are seeking a technically deep, impact-driven ML/AI Scientist with expertise in multimodal data (e.g., genomic, transcriptomic, clinical, and/or imaging) to unlock transformative insights in precision medicine.

As a senior technical leader, you will:
- Lead development of novel ML/AI approaches for translational research and drug development
- Bridge research innovation and production delivery alongside AI engineers, data scientists, clinicians, and product teams
- Leverage unique, large-scale multimodal datasets and high-performance computing infrastructure

Key Responsibilities

Model Research & Development
- Select, fine-tune and optimize foundation models (e.g., LLMs, U-Net, ViT, transformers, GNNs, diffusion/embedding models for multimodal data)
- Prototype and benchmark novel architectures for complex tasks across sequencing, imaging and clinical data
- Build agentic systems to automate sophisticated workflows

Productionization & MLOps
- Design and implement scalable, observable, and maintainable ML pipelines on AWS (SageMaker, EC2/GPU, Lambda, ECS/EKS)
- Containerize models (Docker/Kubernetes), develop APIs or batch services, and integrate into CI/CD workflows
- Contribute to reusable tooling (prompt libraries, feature extractors, evaluation harnesses) and high-performance retrieval strategies (vector DBs, RAG)
- Ensure data governance, privacy and compliance (HIPAA, GDPR) throughout model development and deployment

Scientific Leadership & Collaboration
- Partner with domain experts to define scientific questions, shape the ML roadmap and prioritize strategic data problems
- Rapidly test hypotheses, ship prototypes/MVPs and define evaluation metrics (accuracy, latency, interpretability, robustness, fairness)
- Communicate complex technical concepts clearly to cross-functional stakeholders and drive data-driven decision making

Mentorship & Best Practices
- Provide technical leadership and mentorship to junior engineers and scientists
- Foster best practices in code quality, testing, reproducibility and documentation
- Publish high-impact research in peer-reviewed journals or conferences

Required Qualifications

- PhD in Computer Science, Bioinformatics, Computational Biology, Statistics or equivalent practical experience
- 8+ years applying ML/AI to real-world problems in healthcare, life sciences, genomics or digital pathology
- Proficiency in Python and deep-learning frameworks (PyTorch, TensorFlow or Keras)
- Hands-on experience integrating LLMs and/or computer-vision models into production pipelines
- Strong communication skills with demonstrated cross-functional leadership

Preferred Qualifications
- Prior work with EHR/LIMS data processing or bioinformatics pipelines
- Publications or open-source contributions in biomedical AI / ML
- Familiarity with agent frameworks (e.g., LangChain, MCP) and automated decision-support workflows
- Experience with vector databases and semantic search (Pinecone, Weaviate)
- Hands-on expertise with AWS ML services, container orchestration (Docker, Kubernetes) and API development