Quantitative Researcher - Model Scaling (AI)

Location: San Francisco, California, United States

Salary: $201,000–$261,000 per year, plus eligibility for an annual bonus.

Company

hirify.global provides research-based data, analytics, indexes, and technology that help investors and financial institutions understand risk and opportunity.

What you will do

• Design and build research infrastructure integrating AI into model development, validation, and reporting workflows.
• Develop tools and frameworks that convert high-level research specifications into production-ready implementations.
• Build and maintain automated validation, testing, and governance pipelines for quantitative models.
• Write production-level Python and other software to support platform development and model delivery.
• Support factor and risk models while improving research iteration speed.
• Collaborate with research, engineering, and data teams, and present complex systems to broad audiences.

Requirements

• Master’s degree or Ph.D. in finance, statistics, computer science, engineering, or another quantitative discipline.
• Strong software engineering skills, particularly in Python.
• Hands-on experience with AI-assisted development tools and workflows.
• Experience building systems and tooling that use AI or LLMs to augment technical workflows.
• Experience with data analysis, large-scale data infrastructure, econometrics, and applied statistics.
• Ability to work independently and drive projects from design through delivery.

Nice to have

• Knowledge of finance or risk modeling.

Culture & Benefits

• Flexible working arrangements and collaborative workspaces.
• Comprehensive employee benefits tailored to location.
• Annual bonus eligibility and transparent compensation schemes.
• Learning resources including the AI Learning Center, LinkedIn Learning Pro, and tailored development opportunities.
• Career growth through internal mobility, expanded roles, and multi-directional career paths.
• Inclusive environment supported by employee resource groups.