Machine Learning Engineer I (LLM)

TL;DR

Machine Learning Engineer I (LLM): Designing, building, and deploying large language model applications including RAG systems and agentic platforms with an accent on clinical data infrastructure and model validation pipelines. Focus on ensuring compliance, performance, and patient safety for AI systems deployed across the health system.

Location: Must be based in New York, NY

Salary: $109,000–$163,695 Annually

Company

hirify.global is a leading academic medical system in New York, dedicated to transforming healthcare through innovation, research, and high-quality patient care.

What you will do

• Build and maintain robust ETL pipelines for structured and unstructured clinical data.
• Design and deploy LLM-powered applications including clinical chatbots and decision-support tools.
• Develop RAG pipelines integrating vector databases with clinical knowledge sources.
• Engineer pipelines for pre-deployment model validation and post-deployment monitoring.
• Collaborate with cross-functional teams to ensure AI systems meet compliance and patient safety standards.
• Maintain documentation of data workflows, platform architecture, and validation processes.

Requirements

• Bachelor's degree in Computer Science, Statistics, Mathematics, or related field.
• Knowledge of at least one programming language among Scala, Python, Java, C, or C++.
• Understanding of machine learning algorithms and Software Development Lifecycle.
• Familiarity with SQL or other database languages.
• Ability to work independently and exercise independent judgment in a dynamic environment.

Nice to have

• Master's degree in a quantitative discipline.
• 2+ years of experience in data engineering, software engineering, or machine learning.
• Hands-on experience with LLM-based applications, RAG architectures, and agentic frameworks.
• Proficiency in cloud computing platforms (AWS, Azure, GCP) and DevOps principles.
• Experience with ML lifecycle management tools like MLflow, Kubeflow, or Airflow.

Culture & Benefits

• Commitment to fostering an inclusive and supportive workplace environment.
• Opportunities for professional growth and advancement within a leading academic medical system.
• Focus on innovation and applying new scientific knowledge to complex healthcare challenges.
• Collaborative culture emphasizing respect, fairness, and continuous learning.