Staff Applied Scientist Document Vision
About The Position
The Work Every legal matter is its own experiment. An attorney arrives with a theory of the case; the evidence arrives as hundreds of thousands of documents, sometimes millions, that no one has read and no model has seen. Somewhere in the cross product of the two are the answers that decide lawsuits, investigations, and livelihoods. Finding them quickly and defensibly, with the integrity and credibility attorneys can rely on, is the problem we own. We solve it creatively and rigorously. Relativity is a data-centered, AI-native legal technology company, and Applied Science builds the AI inside Relativity aiR. We launched aiR in 2023 and have now run commercial generative AI in the legal domain for more than three years, powering work that includes the largest investigations in the world. Our systems are distinguished by the data they operate over (more than 93 petabytes) and the work they have done: over 190 million AI review decisions, backed by more than 1 billion generative sub-analyses in 2026 alone. The team is as distinctive as the data: legal experts, all former litigators, work directly inside Applied Science. At Relativity, our mission is to Organize data. Discover the truth. Act on it. The Applied Science team serves this mission by building bold and ambitious AI systems. We are curious, dedicated, and humble. We understand complexity, uphold rigor, and measure relentlessly. We build and ship with pace. Above all, we are interdisciplinary collaborators and team players. We're looking for a Staff Applied Scientist to take on our hardest problems in document vision and set standards that reach beyond a single team.
Requirements
- A master's or PhD in computer science or another quantitative discipline (or equivalent professional experience), and at least 6 years of applied AI/ML experience.
- Years of production AI/ML behind you: systems you specified, shipped, and operated at scale, in partnership with the engineers who run them.
- Expert judgment about AI systems: you've built them, measured them, and formed views of their limits that hold up under challenge.
- Scientific rigor other people borrow: you supervise the data understanding of teams beyond your own, your evaluations become the template, and your error analyses end debates.
- Software-engineering judgment trusted across teams, and the programming skill to credibly prototype what you propose.
- An ownership mindset that extends across the organization.
- Algorithms
- Computer Vision
- Data Analysis
- Data Science
- Deep Learning
- Machine Learning (ML)
- Natural Language
- Natural Language Processing (NLP)
- Python (Programming Language)
- Scientific Research
Nice To Haves
- Experience with vision-language or document-understanding models (layout analysis, OCR-adjacent pipelines, table and figure extraction) in production.
- An interest in legal technology and the justice system.
- Experience developing information retrieval systems.
- Experience developing agentic harnesses.
- Experience building reliable AI systems at scale.
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.
Benefits
- competitive base salary
- annual performance bonus
- long-term incentives
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What This Job Offers
Job Type
Full-time
Career Level
Senior
