Senior Director, Applied Science

Posting Type

Hybrid

Job Overview

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 Director, Applied Science to own applied science across EMEA from our Poland office: AI system strategy, portfolio, and people.

Job Description and Requirements

Capable and reliable

Two requests can look nearly identical and be worlds apart. "See if you can find me an example of this" needs a capable system: it finds the example or it doesn't. "Conduct a reasonable search for any and all documents responsive to this request" is a different kind of promise. Its answer spans a corpus no one will ever read end-to-end. So the system's process, as much as its output, has to earn the trust of the professionals who rely on it. That property is reliability. It decomposes into consistency, robustness, calibration, and safety: systems that behave tomorrow the way they did today, degrade predictably under stress, know how confident they should be, and check their own work. Before aiR returns an analysis, it validates its citations and runs internal consistency checks; when a check fails, it refuses to answer. It has refused more than a million times so far in 2026, and we count every one as a success: an error caught before it reached a user. Your domains will build for both, and you'll own the operating model that makes it hold.

The focus: Poland

Applied science in Poland is entering its next phase of growth. The role sits in Poland; its span is EMEA. You'll be the single-threaded owner for AI system strategy, evaluation, and scientific decision-making across our agentic assistant for search and legal data intelligence, data science for product insights, and AI efficiency. You'll also lead the site's applied-science capability itself: growing the team, deepening its partnership with our Poland engineering organization, and carrying Relativity's legal technology strategy across the region, with candidates, at events, and with customers.

What you'll do

• Own the domains as their single-threaded owner: AI system strategy, evaluation standards, and scientific decision-making across the agentic assistant, product insights, and AI efficiency.
• Lead leaders: managers, staff scientists, and principal scientists. Build the bench that builds the systems.
• Own the portfolio: what your organization invests in, what it stops, and what it promises to the business.
• Set the operating model: how work moves from idea to production, and how quality is enforced at each gate.
• Grow the site: recruit and develop Poland's applied-science talent, and deepen the partnership with our Poland engineering organization.
• Stay technically credible: review the decisive evaluations and architectures yourself; your judgment is part of the site's quality system.
• Represent Relativity's AI strategy across EMEA, and represent the Poland organization to executives, customers, and partners.

What you bring

• A master's or PhD in computer science or another quantitative discipline (or equivalent professional experience), and at least 8 years in applied AI/ML, with a track record of leading teams.
• A track record of delivering AI products at scale: from AI system strategy through production operation, in partnership with engineering and product organizations.
• Experience leading leaders and growing scientists and managers into larger roles.
• AI-system judgment at portfolio stakes: you decide what is ready to ship and what needs more evidence, and you can defend either call.
• Machine-learning rigor you can institutionalize: standards an organization keeps even when you're not in the room.
• Executive-grade communication: you can carry a technical judgment into a boardroom or a customer escalation and land it.
• Professional English proficiency, written and spoken.

Nice to have

Experience growing a technology site or founding team; an interest in legal technology and the justice system; experience building reliable AI systems at scale; multi-office or global team leadership.

Why Relativity Applied Science

This is the place where your curiosity, dedication, and talent will build products that power the pursuit of justice around the world.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

533 000 and 799 000PLN

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position. 

Required Skills:

Big Data, Communication, Data Science, Experimentation, Natural Language, Reinforcement Learning, Research and Development, Science, Statistical Models, Technical Leadership