Senior Machine Learning Engineer

Grab your cape, become a SuperHyro!

Hyro, the leader in Responsible AI Agents for Healthcare, enables health systems to safely automate workflows and conversations across their most valuable platforms, services, and channels—including call centers, websites, SMS, mobile apps, and more. Hyro's clients, which include Intermountain Health, Baptist Health, and Hackensack Meridian Health, benefit from AI agents that are fully HIPAA-compliant, fast to deploy, easy to maintain, and simple to scale—generating better conversations, successful patient outcomes, and revenue-driving insights.

What Are We Looking For?

We’re seeking a passionate Senior Machine Learning Engineer to join our AI team. With a wide array of responsibilities and corresponding impact, you’ll help spearhead our new product offering and the world-class AI conversation product impacting millions of patients.

Responsibilities:

• Design, develop, and drive design processes and products that incorporate Generative AI (LLMs), models and knowledge Retrieval in order to help patients across the US.
• Design and define data pipelines and evaluation pipelines.
• Build applicative AI in production on a large scale.
• Build solutions for different mediums, including voice products with minimal latency and high accuracy.
• Provide a scientific evaluation of the quality of our models..
• Continuously improve our existing NLP capabilities to help patients across the US answer any question, schedule appointments with their doctor, refill their prescriptions, and much more.
• Use best practices and SOTA from the AI industry, but also push the envelope to new heights.
  
  

• 5+ years of experience in Data Science or an equivalent role. Experience in developing ML / DL / LLM / NLP algorithms.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field, with a significant focus on machine learning.
• High proficiency in Python.
• Excellent understanding of machine learning techniques, algorithms, and methodology.
• Experience with common data science toolkits, such as Pandas, Scikit-learn, Tensorflow, and more.
• High-level applied statistics skills, such as distributions, statistical testing, etc.
• Experience in data mining and insight drawing from large data sets.
• Data-oriented personality, analytical mind, and problem-solving aptitude.
• Experience in Constraint programming or Network science - an advantage.
• A team player with a can-do attitude, delivery-oriented.