The company is looking to implement advanced AI models across clinical and genomics applications to drive real-world results in precision medicine.
Requirements
- Proficiency in deep learning frameworks such as PyTorch, TensorFlow, or Keras
- Experience with integrating LLMs (e.g., OpenAI, LLaMA, DeepSeek, Claude) into downstream clinical workflows
- Expertise in fine-tuning and optimizing pre-trained models for domain-specific applications
- Familiarity with agent frameworks (e.g., LangChain, Haystack, ReAct) and retrieval-augmented generation (RAG) techniques
- Experience with semantic search, hybrid search, and vector databases
- Strong programming skills in Python; familiarity with libraries such as scikit-learn, pandas, and NumPy
- Experience with containerization (Docker) and orchestration (Kubernetes)
Responsibilities
- Model Selection, Tuning and Deployment
- Agent and Workflow Development
- Iteration and Evaluation
- Engineering and Collaboration
- Security and compliance: Ensure all model pipelines adhere to data governance, privacy, and compliance standards in healthcare and genomics
Other
- PhD in Computer Science, Computational Biology, Bioinformatics, Statistics, or related field, or equivalent practical experience
- 8+ years of experience applying machine learning to real-world problems, preferably in healthcare or genomics domains
- Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents
- 401k benefits, commuter benefits and much more
- Pregnancy and baby bonding leave
