Artificial Intelligence Engineer

TAPPS is building the next generation of cancer surveillance technology to improve outcomes for cancer survivors. They are seeking an exceptional AI Engineer to design, build, and deploy machine learning systems that transform complex biomedical data into actionable clinical insights.

Responsibilities:

• Design, develop, train, evaluate, and deploy machine learning models for:
• Cancer biomarker detection
• Risk stratification
• Longitudinal patient monitoring
• Personalized screening and survivorship recommendations
• Translate research models into reliable, production-ready systems
• Develop and optimize deep learning architectures, including foundation models and multimodal learning approaches
• Build scalable machine learning pipelines covering:
• Data ingestion
• Feature engineering
• Model training
• Model serving
• Performance monitoring
• Develop cloud-based ML infrastructure using platforms such as AWS or GCP
• Leverage GPU/accelerated computing environments for large-scale model development
• Implement strong engineering practices including:
• Version control
• Testing
• CI/CD
• Containerized deployments (Docker)
• Partner with clinical and data teams to curate, validate, and manage complex datasets from sources including:
• Genomics
• Medical imaging
• Electronic health records (EHR)
• Other multimodal healthcare data sources
• Build evaluation frameworks to ensure model performance, reliability, and clinical relevance
• Collaborate with clinicians and scientific stakeholders to align AI capabilities with real-world healthcare workflows
• Bridge cutting-edge AI research with practical clinical applications
• Support development and refinement of AI systems as the platform evolves
• Contribute to technical strategy and architecture decisions as an early engineering team member