Staff Applied Scientist — Remote/Hybrid Document Vision AI

Relativity; Bridgeport (CT); Hybrid; USD 197,000 - 295,000; Full time

Job summary

Relativity is a data-centered, AI-native legal technology company. We seek a Staff Applied Scientist to tackle the hardest document-vision problems and set cross-team standards for rigorous and reliable AI.

You will own multimodal document understanding from vision-language modeling to evaluation, and mentor senior scientists while partnering with engineering and the Applied Science leadership to push frontiers in legal tech AI.

Qualifications

• Master’s or PhD in computer science or a quantitative discipline.
• 6+ years of applied AI/ML experience.
• Production AI/ML systems: designed, shipped, and operated at scale.
• Strong judgment about AI systems: evaluation templates and limits.
• Software‑engineering judgment and credible prototype skills.
• Ownership mindset across the organization.

Responsibilities

• Tackle the hardest, most ambiguous problems and produce a clear, well-specified approach and an evaluative plan.
• Set standards for evaluation methods, modeling patterns, and quality across scientists.
• Own readiness for flagship AI systems from problem framing through efficacy studies and production monitoring.
• Mentor senior and lead scientists to multiply the team's impact.
• Advise Applied Science leadership on future directions and investments.

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 a quantitative discipline

Job description

Relativity is a data-centered, AI-native legal technology company. We seek a Staff Applied Scientist to tackle the hardest document-vision problems and set cross-team standards for rigorous and reliable AI.

You will own multimodal document understanding from vision-language modeling to evaluation, and mentor senior scientists while partnering with engineering and the Applied Science leadership to push frontiers in legal tech AI.