ML Engineer II

NYU Langone Health•New York, NY

About The Position

The MCIT Applied AI team at NYU Grossman School of Medicine is at the forefront of transforming healthcare delivery through the integration of emerging technologies. This role is for an ML Engineer to join their clinical innovation hub, dedicated to assessing the technical and clinical feasibility of innovative AI approaches within the NYU Langone ecosystem. The successful candidate will be responsible for building the technical scaffolding required to prototype, benchmark, and validate these technologies before they are scaled across the health system.

Requirements

Bachelor's degree or equivalent in computer science, engineering, mathematics, statistics, data science, or related field.
0-1+ Years of Experience.
Proficient in Python and common machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
Familiar with machine learning concepts and techniques such as supervised and unsupervised learning, classification, regression, clustering, dimensionality reduction, etc.
Experience with data analysis, visualization, and manipulation tools such as Pandas, Numpy, Matplotlib, etc.
Knowledge of SQL and relational databases.
Good understanding of software engineering principles and practices such as version control, testing, debugging, etc.
Strong communication and teamwork skills.
Curious and eager to learn new technologies and methods.

Nice To Haves

Education: Masters degree in Data Science, Computer Science, or a related field (or a Bachelors with 3+ years of equivalent experience).
Experience: 1.5+ years of hands-on experience in data engineering or a data-heavy backend role.
Technical Proficiency: Mastery of the Python data stack (Pandas, Scikit-learn, NumPy). Ability to write complex SQL joins and window functions to extract data from large-scale databases (e.g., Epic Clarity).
Independent Execution: Proven ability to build data pipelines from scratch and execute standard ML workflows with minimal daily supervision.
ML Rigor: Strong understanding of model evaluation metrics (AUC, F1-score, Precision-Recall) and basic statistical significance testing.
Healthcare Fluency: Basic understanding of clinical data structures (EHR tables, ICD-10, CPT codes).
Deep Learning: Experience implementing, training, and fine-tuning deep learning models.
Advanced AI: Experience building or evaluating modern AI models, such as AI Agents or RAG systems, is a significant advantage.
Cloud Architecture: Familiarity with Databricks or Azure/AWS healthcare cloud environments.
MLOps Familiarity: Experience with Docker, Kubernetes, or CI/CD pipelines is an advantage, but not critical.

Responsibilities

ML Model Execution: Independently set up and run standard machine learning models (e.g., Random Forests, XGBoost, or baseline NLP models) on healthcare datasets to validate feasibility and establish performance baselines.
Pipeline Development (ELT/ETL): Independently design and implement reliable data pipelines to ingest clinical and operational data. You will focus on efficient data movement and transformation using SQL and Python to create analysis-ready datasets.
Benchmarking & Validation: Develop automated benchmarking suites to evaluate the performance, safety, and bias of new AI models against current clinical gold standards.
Infrastructure & Security Integration: Collaborate with MCIT Security teams to ensure innovative AI tools meet HIPAA, SOC2, and internal governance standards during the pilot phase.
Documentation & Reproducibility: Maintain high-quality code repositories and documentation so that every experiment is fully reproducible.

Benefits

comprehensive benefits and wellness package
robust support system for any stage of life
support for developing your career
support for starting a family
support for saving for retirement
financial security benefits
generous time-off program
employee resources groups for peer support
holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care
extensive resources and services designed to enhance your overall quality of life for you and your family