Machine Learning Engineer ll (AI)

TL;DR

Machine Learning Engineer ll (AI): Designing, deploying, and monitoring production ML models for clinical findings from structured and unstructured data sources with an accent on building reliable and scalable systems. Focus on feature engineering, statistical analysis, and developing novel ML techniques using modern language models like LLMs.

Location: Fully remote within the United States with about 5% travel.

Salary: $120,000–$140,000 annually

Company

hirify.global provides an AI-powered clinical intelligence platform that streamlines healthcare access, improves payer-provider collaboration, and optimizes healthcare economics.

What you will do

• Design, develop, and deliver clinical ML models based on in-depth healthcare data analysis.
• Build reliable and scalable production machine learning systems.
• Work on feature engineering, statistical analysis, and novel ML techniques to improve model performance and runtime.
• Collaborate cross-functionally with product managers, statisticians, clinicians, and clinical analysts.

Requirements

• 2-4 years of full-time professional experience in Machine Learning.
• MS in computer science, machine learning, computational linguistics, statistics, mathematics, or a similar field.
• Hands-on experience building with modern language models, including context-engineering LLMs or fine-tuning SLMs.
• Ability to independently perform experimental design, data collection, measurement, and interpretation of results.
• Experience configuring, training, evaluating, deploying, and maintaining models in a production setting.
• Advanced proficiency in Python and familiarity with ML frameworks such as PyTorch.

Culture & Benefits

• Fully remote opportunity with about 5% travel.
• Comprehensive medical, dental, vision, life, and disability insurance.
• 401K retirement plan with company match and flexible spending/health savings accounts.
• Up to 184 hours (23 days) of PTO per year plus company holidays.
• Up to 14 weeks of paid parental leave and pet insurance.
• Supportive, growth-oriented environment with diverse, inclusive teams.

Hiring process

• Preliminary Phone Screening with Talent Acquisition.
• Interview(s) with Hiring Manager and Behavioral interviews.
• Live Coding session.
• Case Study.