Machine Learning & AI Analyst (Clinical Research) - Data Driven & Digital Medicine

Location: New York, NY; hybrid flexibility may be available according to departmental policy

Salary: $87,692–$131,538 annually

Company

hirify.global is a large academic medical system focused on patient care, medical education, clinical research, and healthcare innovation.

What you will do

• Lead NLP and multimodal machine learning initiatives using clinical notes, EHR data, imaging, biosignals, and multi-omics.
• Prototype decision-support, workflow triage, quality improvement, and operational productivity tools.
• Build robust data pipelines and features with strong data integrity, lineage, and reproducibility.
• Train, fine-tune, and evaluate traditional ML, deep learning, LLM, and retrieval-augmented generation models.
• Partner with clinicians, scientists, and operations leaders to define problems, success criteria, and pilot evaluations.
• Operationalize models through versioning, CI/CD, monitoring, governance, documentation, and responsible-use practices.

Requirements

• Bachelor’s degree in computer science, biomedical or clinical informatics, data science, statistics, engineering, or a related field; a master’s degree is preferred.
• At least 2 years of experience working with machine learning or NLP using Python and/or R, plus strong SQL skills.
• Hands-on experience with scikit-learn, PyTorch or TensorFlow, spaCy or Hugging Face, experiment tracking, and reproducible workflows.
• Ability to translate clinical or operational problems into analytical solutions and communicate results to technical and non-technical audiences.
• Experience or understanding of privacy, security, HIPAA compliance, model governance, fairness, and human-in-the-loop evaluation.

Nice to have

• Deep experience with NLP, LLM prompting, fine-tuning, evaluation, and RAG over clinical knowledge bases.
• Experience with multi-omics modalities, EHR data, and standards such as OMOP.
• Experience with MLflow, Weights & Biases, Docker, Kubernetes, and cloud platforms.
• Experience delivering prototypes or products used by clinicians or researchers; publications and open-source contributions are a plus.

Culture & Benefits

• Work in an academic medical system combining hospitals, laboratories, schools, and clinical research.
• Contribute to responsible AI, digital medicine, education, and clinical innovation.
• Collaborate with clinicians, scientists, operations partners, and technical stakeholders.
• Participate in an environment focused on inclusion, fairness, professional growth, and high-quality patient care.