Principal AI Scientist

Principal AI Scientist

Role Overview
We are seeking a technically deep, impactdriven MLAI Scientist with expertise in multimodal data (e.g., genomic, transcriptomic, clinical, andor imaging) to unlock transformative insights in precision medicine.

As a senior technical leader, you will:
Lead development of novel MLAI approaches for translational research and drug development
Bridge research innovation and production delivery alongside AI engineers, data scientists, clinicians, and product teams
Leverage unique, largescale multimodal datasets and highperformance computing infrastructure

Key Responsibilities

Model Research & Development
Select, finetune and optimize foundation models (e.g., LLMs, UNet, ViT, transformers, GNNs, diffusionembedding 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, EC2GPU, Lambda, ECSEKS)
Containerize models (DockerKubernetes), develop APIs or batch services, and integrate into CICD workflows
Contribute to reusable tooling (prompt libraries, feature extractors, evaluation harnesses) and highperformance 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 prototypesMVPs and define evaluation metrics (accuracy, latency, interpretability, robustness, fairness)
Communicate complex technical concepts clearly to crossfunctional stakeholders and drive datadriven 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 highimpact research in peerreviewed journals or conferences

Required Qualifications

PhD in Computer Science, Bioinformatics, Computational Biology, Statistics or equivalent practical experience
8+ years applying MLAI to realworld problems in healthcare, life sciences, genomics or digital pathology
Proficiency in Python and deeplearning frameworks (PyTorch, TensorFlow or Keras)
Handson experience integrating LLMs andor computervision models into production pipelines
Strong communication skills with demonstrated crossfunctional leadership

Preferred Qualifications
Prior work with EHRLIMS data processing or bioinformatics pipelines
Publications or opensource contributions in biomedical AI ML
Familiarity with agent frameworks (e.g., LangChain, MCP) and automated decisionsupport workflows
Experience with vector databases and semantic search (Pinecone, Weaviate)
Handson expertise with AWS ML services, container orchestration (Docker, Kubernetes) and API development