Relativity
At Relativity, we build the most innovative and comprehensive tools for making sense of unstructured data. When more people can find the facts in mountains of documents, emails, and texts, more legal and data-centric matters can be resolved equitably. Join us in our mission to help our customers organize data, discover the truth, and act on it.
Are you looking for a hybrid or remote work opportunity? Are you interested in a workplace that allows for flexibility in your day? Are you ready for a workplace that provides benefits that suit your needs?
Every year, the global justice system benefits from the insights of Relativity AI on billions of documents– and we are just getting started on our journey to use AI to improve each user experience, product, legal matter, and investigation at Relativity. We are focused on helping our users discover the truth more quickly, organize their data, and act on it with confidence.
Relativity has established a set of AI Principles to guide product development and underscore their commitment to developing responsible AI. These principles include building AI with purpose that delivers value for customers, empowering customers with clarity and control, ensuring fairness in AI development, championing privacy, placing the security of customers’ data at the heart of everything they do, and acting with a high standard of accountability.
As a team, we believe in exploration, experimentation, and bringing your curiosity to work every day. We know that you can’t innovate without experimentation — and a little failure happens on the path to invention. We use the latest and greatest to ensure we are the best. We experiment, ship, and learn every day.
About the AI Team at Relativity
Relativity is heavily invested in developing new AI products and features for our customers. Our team spans across many teams and functions across Relativity Engineering, including our data engineering team, ML Ops team, applied science team, and product-focused feature teams for our RelOne AI suite of products.
About the Senior Applied Scientist, Generative AI Role
The Senior Applied Scientist, Generative AI will develop generative and machine-learning products for the eDiscovery industry in close collaboration with their applied science, product, design, and engineering team. You will use your experience in applied science to build models that help legal professionals organize data, discover the truth, and act on it. Relativity is the recognized leader of AI in eDiscovery, as well as the builder of the market’s leading product, Relativity One. As a Senior Applied Scientist, you will contribute to our balanced portfolio of research, development, and operation of transformational generative AI technologies according to the responsible AI approach laid out by our AI Principles.
Job Description and Requirements
Responsibilities:
Minimum Qualifications:
Preferred Qualifications:
Relativity is a diverse workplace with different skills and life experiences—and we love and celebrate those differences. We believe that employees are happiest when they're empowered to be their full, authentic selves, regardless how you identify.
Benefit Highlights:
Comprehensive health plan
Flexible work arrangements
Two, week-long company breaks per year
Unlimited time off
Long-term incentive program
Training investment program
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.
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:
zł216 000 and zł324 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.
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