Senior Applied Scientist

Senior Applied Scientist, Generative AI Relativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy, trust, and accountability are critical. Every year, the global justice system benefits from insights generated by Relativity AI across billions of documents. We are just getting started on our journey to use AI to improve the outcome of every discovery, investigation, and analysis performed on our platform. At Relativity, we develop AI guided by our AI Principles. These principles ensure we build AI with clear purpose, empower customers with transparency and control, treat fairness and privacy as first principles, protect customer data by design, and act with a high standard of responsibility and accountability. The Applied Science team operates at the core of Relativity's AI development. Our team includes specialists with advanced postgraduate training and deep experience building and operating machine learning models at scale. We work closely with engineering, product, design, data engineering, machine learning operations, and LLM engineering teams to translate complex AI research into production-ready features used by legal professionals around the world. Job Description and Requirements About The Role As a Senior Applied Scientist, Generative AI, you will design, build, and deploy generative and machine learning models that power Relativity's next generation of AI-driven product capabilities. You will collaborate closely with applied scientists, engineers, product managers, and designers to build models that help legal professionals organize data, discover the truth, and act on it with confidence. This role balances research, development, and operational responsibility. You will contribute to Relativity's portfolio of transformational generative AI technologies while adhering to our responsible AI principles and ensuring models perform reliably in real-world, high-stakes environments. What You'll Do Develop machine learning and generative AI models that ship as customer-facing product features Collaborate closely with engineers to write production-quality code and contribute across the full model deployment lifecycle Design and evaluate models that operate at very large scale, including search and retrieval systems spanning hundreds of millions to billions of documents Contribute to internal standards, processes, and tooling for building, evaluating, and deploying generative AI systems Partner with Product and Data teams to assemble, curate, and synthesize datasets for model development and evaluation Conduct rigorous experimentation, model evaluation, and iteration to improve model quality, explainability, safety, and performance Collaborate across AI, engineering, and product teams to ensure models integrate effectively into larger systems Apply Relativity's AI Principles to ensure responsible, fair, secure, and transparent AI development Communicate complex data science and machine learning concepts clearly and effectively to collaborators with diverse technical backgrounds What We're Looking For Required Experience building search or retrieval systems operating at the scale of hundreds of millions of documents Experience developing and applying generative AI models as part of larger, domain-specific systems Experience across the full machine learning lifecycle, including experimentation, evaluation, deployment, and iteration Experience working in containerized environments using Kubernetes-based tooling and workflows Interest in or experience with the legal industry, eDiscovery, or the broader justice system Strong programming ability in a language such as Python Comfort working in UNIX-based environments using command-line tools Ability to communicate complex data science concepts thoughtfully and inclusively to a wide range of stakeholders Preferred Master's degree in Computer Science or a quantitative field plus 2 years of relevant industry experience OR Ph.D. in Computer Science or a quantitative field OR the equivalent of 5 years of relevant academic and/or industry experience Experience building and deploying systems that leverage large language models Experience contributing to shared data science or ML engineering standards, tooling, or best practices Why We Could Be a Great Fit Impactful Mission: Your work directly contributes to improving outcomes across the global justice system by helping customers uncover critical insights in massive, complex datasets. AI at Real Scale: You'll work on some of the largest and most complex AI systems in the legal technology market, operating at significant data and computational scale. Growth and Collaboration: You'll collaborate closely with experienced applied scientists, engineers, and product leaders while continuing to grow your expertise in generative AI and production machine learning systems. Responsible AI Culture: You'll be part of an organization deeply committed to building AI that is ethical, transparent, secure, and accountable. Inclusive Environment: We value diverse perspectives, backgrounds, and ways of thinking, and believe they make our teams and products stronger. Compensation and Benefits: Competitive compensation, health and retirement benefits, discretionary time off (DTO), parental leave for primary and secondary caregivers, company-wide breaks, wellness resources, and an equity program. 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 $146,000 and $218,000. 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: Algorithms, C++ Programming Language, Computer Vision, Data Science, Deep Learning, Machine Learning (ML), Natural Language, Python (Programming Language), Researching, Statistical Models