Staff Applied Scientist — Document Vision (Remote/Hybrid)

Relativity; Indianapolis (IN); Hybrid; USD 197,000 - 295,000; Full time

Benefits offered by this job

Annual bonus

Long-term incentives

Job summary

Relativity Applied Science seeks a Staff Applied Scientist to tackle the hardest problems in document vision, driving multimodal understanding and evaluation standards at scale. You will shape AI systems for defense of evidence in legal contexts and work with engineers to ship reliable solutions.

You will mentor senior scientists, define modeling patterns and quality bars, and advise leadership on strategic investments as the team grows in a data-centered, legal-tech environment.

Qualifications

• Master’s or PhD in computer science or a quantitative discipline with 6+ years of applied AI/ML experience.
• Experience shipping and operating AI systems at scale in collaboration with engineers.
• Ability to evaluate AI systems, articulate limits, and justify decisions.

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 or PhD in computer science or quantitative discipline

Job description

Relativity Applied Science seeks a Staff Applied Scientist to tackle the hardest problems in document vision, driving multimodal understanding and evaluation standards at scale. You will shape AI systems for defense of evidence in legal contexts and work with engineers to ship reliable solutions.

You will mentor senior scientists, define modeling patterns and quality bars, and advise leadership on strategic investments as the team grows in a data-centered, legal-tech environment.