Staff Applied Scientist — Document Vision Leader

Relativity; New York (NY); Hybrid; USD 197,000 - 295,000; Full time

Job summary

Relativity seeks a Staff Applied Scientist to tackle the toughest problems in document vision. You will own the science from vision-language modeling to evaluation standards, building reliable AI systems at scale and mentoring senior scientists.

You’ll work in a data-centered, AI-native environment with a history of large-scale AI review decisions and defensible evidence for legal matters. Expect competitive compensation and ongoing innovation.

Qualifications

• Master’s or PhD in computer science or a quantitative field with substantial AI/ML experience.
• Proven track record shipping and operating AI/ML systems at scale.
• Strong scientific rigor and ability to lead evaluations and error analyses.

Responsibilities

• Take on the hardest, most ambiguous problems in the portfolio and produce clarity: a well-specified approach, an evaluation that settles the question, a system that ships.
• Set standards that reach beyond your team: evaluation methods, modeling patterns, and quality bars adopted by scientists you’ve never worked with.
• Own readiness for flagship AI systems, from problem framing through efficacy studies and production monitoring, in partnership with engineering.
• Multiply the team through deep review and mentorship of senior and lead scientists.
• Advise Applied Science leadership on where the science is going and where we should invest.

Skills

Algorithms

Computer Vision

Data Analysis

Data Science

Deep Learning

Machine Learning

Natural Language

Natural Language Processing

Python

Scientific Research

Education

Master’s degree in Computer Science

PhD in Computer Science

Job description

Relativity seeks a Staff Applied Scientist to tackle the toughest problems in document vision. You will own the science from vision-language modeling to evaluation standards, building reliable AI systems at scale and mentoring senior scientists.

You’ll work in a data-centered, AI-native environment with a history of large-scale AI review decisions and defensible evidence for legal matters. Expect competitive compensation and ongoing innovation.