Staff Applied Scientist: Multimodal Document AI

Relativity; Phoenix (AZ); Hybrid; USD 197,000 - 295,000; Full time

Job summary

Relativity Applied Science is building bold AI systems to power the pursuit of justice. This Staff Applied Scientist role focuses on document vision, scaling multimodal understanding, and establishing robust evaluation standards that ensure defensible results.

You will own research across vision-language modeling, evaluation metrics, and integration with production systems, while mentoring senior scientists to amplify impact.

Qualifications

• A master’s or PhD in computer science or another quantitative discipline, or equivalent experience.
• At least 6 years of applied AI/ML experience.
• Production AI/ML: systems specified, shipped, operated at scale with engineers.
• Expert judgment about AI systems and their limits.
• Software-engineering judgment and credible prototyping.
• Ownership mindset across the organization.

Responsibilities

• Take on the hardest, most ambiguous problems and produce clarity: a well-specified approach, an evaluation, a shippable system.
• Set standards beyond your team: evaluation methods, modeling patterns, quality bars.
• Own readiness for flagship AI systems, from framing to production monitoring in partnership with engineering.
• Mentor senior and lead scientists to multiply the team’s capability.
• Advise leadership on where science is headed and where to invest.

Skills

Algorithms

Computer Vision

Data Analysis

Data Science

Deep Learning

Machine Learning

Natural Language

Natural Language Processing

Python

Scientific Research

Education

Master's or PhD in computer science or quantitative field

Job description

Relativity Applied Science is building bold AI systems to power the pursuit of justice. This Staff Applied Scientist role focuses on document vision, scaling multimodal understanding, and establishing robust evaluation standards that ensure defensible results.

You will own research across vision-language modeling, evaluation metrics, and integration with production systems, while mentoring senior scientists to amplify impact.