Job Description

Responsibilities

• Translate clinical and business informatics challenges into scoped AI/ML problem statements with measurable success criteria
• Design and build ML pipelines encompassing data ingestion, feature engineering, training, and evaluation with production engineers
• Conduct experiments, benchmarks, and ablation studies to validate model performance and guide decisions
• Partner across clinical informatics, data engineering, and ML teams to integrate models into real workflows
• Document research findings and communicate model behavior, limitations, and performance to technical and non-technical stakeholders

Requirements

• Bachelor's degree in Computer Science, Machine Learning, Data Science, Biomedical Informatics, Statistics, or related field; Master's or Ph.D. preferred
• 4–6 years progressive experience in applied AI/ML with independent model development and evaluation
• Proficiency in Python scientific ML stack including scikit-learn, HuggingFace Transformers, pandas, NumPy
• Strong foundation in supervised, unsupervised, self-supervised learning, and deep neural networks with modern frameworks
• Experience designing and evaluating NLP or multimodal models, including LLM fine-tuning or prompt engineering
• Familiarity with health/life sciences data such as EHR/EMR, clinical notes, genomic, or imaging data
• Experience with experiment tracking, model versioning, and reproducible research practices

Compensation: $150,500–$245,000 annually

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