Staff Applied Scientist: Multimodal Document Vision-Remote

Relativity; Washington (Washington County); Hybrid; USD 197,000 - 295,000; Full time

Job summary

Relativity is seeking a Staff Applied Scientist to tackle the hardest problems in document vision and set standards that reach beyond a single team. You’ll own the science of multimodal document understanding across aiR, from vision-language modeling to the evaluation standards that make visual evidence usable and defensible.

In this remote/hybrid role, you will guide readiness for flagship AI systems, frame problems, run efficacy studies, and partner with engineering to monitor production.

Qualifications

• Master’s or PhD in computer science or equivalent experience.
• At least 6 years of applied AI/ML experience.
• Production AI/ML experience at scale with systems you specified, shipped, and operated.
• Strong evaluation templates and data understanding supervision.
• Software engineering judgment trusted across teams.
• Ownership mindset across the organization.

Responsibilities

• Tackle the hardest, most ambiguous problems and deliver a clear, shippable solution.
• Set cross-team evaluation methods, modeling patterns, and quality bars.
• Own readiness for flagship AI systems from problem framing to production monitoring.
• Mentor senior and lead scientists through deep reviews.
• Advise Applied Science leadership on future directions and investments.

Skills

Applied AI/ML experience

Production AI/ML at scale

AI system evaluation

Software engineering judgment

Ownership mindset

Mentorship of senior scientists

Education

Master's or PhD in computer science

Tools

Python

Vision-Language Models

Document Understanding

Job description

Relativity is seeking a Staff Applied Scientist to tackle the hardest problems in document vision and set standards that reach beyond a single team. You’ll own the science of multimodal document understanding across aiR, from vision-language modeling to the evaluation standards that make visual evidence usable and defensible.

In this remote/hybrid role, you will guide readiness for flagship AI systems, frame problems, run efficacy studies, and partner with engineering to monitor production.