Staff Applied Scientist - Multimodal Document Vision

Relativity; Arizona; Hybrid; USD 197,000 - 295,000; Full time

Job summary

Relativity Applied Science is seeking a Staff Applied Scientist to tackle the hardest document-vision problems and set standards that extend beyond a single team. You will own the science of multimodal document understanding, from vision-language modeling to evaluation standards that ensure evidence is usable and defensible.

You will mentor senior scientists, shape evaluation methods, and partner with engineering to readiness flagship AI systems, driving impact across the organization.

Qualifications

• Master's or PhD in computer science or a quantitative discipline (or equivalent experience).
• At least 6 years of applied AI/ML experience.
• Production AI/ML experience at scale in partnership with engineers.
• Strong judgment about AI systems and their limits.
• Proven capability to supervise data understanding and lead evaluations.
• Software-engineering judgment and credible prototyping skills.
• Ownership mindset across the organization.

Responsibilities

• Take on the hardest, most ambiguous problems in the portfolio and deliver a clear plan and a shippable system.
• Set standards for evaluation methods, modeling patterns, and cross-team quality bars.
• Own readiness for flagship AI systems from framing to production monitoring in collaboration with engineering.
• Mentor senior scientists and lead reviews to multiply impact across the team.
• Advise Applied Science leadership on future directions and investments in AI.

Skills

Algorithms

Computer Vision

Data Analysis

Data Science

Deep Learning

Machine Learning

Natural Language Processing

Python

Scientific Research

Education

Master's degree in computer science

PhD in quantitative field

Job description

Relativity Applied Science is seeking a Staff Applied Scientist to tackle the hardest document-vision problems and set standards that extend beyond a single team. You will own the science of multimodal document understanding, from vision-language modeling to evaluation standards that ensure evidence is usable and defensible.

You will mentor senior scientists, shape evaluation methods, and partner with engineering to readiness flagship AI systems, driving impact across the organization.