Applied Scientist (AI)

TL;DR

Applied Scientist (AI): Researching, designing, and deploying machine learning models for hirify.global’s home-shopping experience with an accent on ranking, recommendation systems, and generative AI. Focus on building scalable models, leveraging LLMs for conversational search, and managing the full model lifecycle from ideation to production.

Location: Must be based in the United States

Salary: $129,500–$217,700 annually (location-dependent)

Company

hirify.global is the most-visited real estate platform in the U.S., dedicated to helping customers navigate buying, selling, financing, and renting homes through innovative digital marketplace solutions.

What you will do

• Research, design, and prototype machine learning models for search, ranking, and recommendations.
• Lead the full model lifecycle, including offline experimentation, A/B testing, and performance monitoring.
• Develop novel modeling approaches using deep learning and large language models (LLMs).
• Apply cutting-edge AI techniques like RAG-style systems to improve property search experiences.
• Optimize home display relevance and context for millions of users.
• Collaborate with cross-functional teams including data engineering, product, and design.

Requirements

• Must be based in the United States
• Experience in designing and training machine learning models for real-world business problems.
• Proficiency in Python and common ML libraries like PyTorch, TensorFlow, or scikit-learn.
• Experience with distributed data systems such as Spark, Hive, or Databricks.
• Demonstrated expertise in search, information retrieval, recommender systems, or generative AI.
• Master’s or PhD in Computer Science, AI, Data Science, or equivalent industry experience.

Culture & Benefits

• Competitive base salary and equity awards.
• Inclusive and innovative work environment recognized as a top workplace.
• Commitment to professional growth and career development.
• Supportive culture that values diverse perspectives and non-traditional backgrounds.