Staff Applied Scientist

Posting Type

Hybrid

Job Overview

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 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 Staff Applied Scientist

The Staff Applied Scientist will join the nascent Polish branch of the Applied Science team and help it build a solid footprint of impact and expertise. You will help shape our AI strategy and deliver its crucial components by collaborating with our customers and cross-functionally within the organisation. Your deep expertise in product and decision data science as well as the ability to leverage new technology will contribute to the value added for our customers and spark innovation within the company. We are looking for a strong generalist who thrives in high-impact and high-visibility environments.

Job Description and Requirements

Responsibilities:  

• Represent Relativity’s AI strategy, key product efforts, and teams/functions in Poland. 

• Partner with management to set and communicate team goals and vision aligned to business requirements. 

• Stay on top of current research and SOTA in (Gen)AI and data science and leverage this knowledge to drive innovation. 

• Be able to choose the best modelling approach for the problem at hand, know how to avoid ‘shooting a fly with a cannon’. 

• Ideate and develop internal standards, processes and tooling for leveraging Generative AI. 

• Mentor talent within the AI engineering team to promote career development, risk taking, innovation, and create a culture of learning. 

• Display an ownership mindset; be accountable for and beyond the features your team and larger organization develops. 

• Lead collaboration with our engineering teams, applied scientists, and product managers to bring ideas from proof of concept to scalable solutions.  

• Prioritize technical investments roadmap and help prioritize tech debt and architecture investments. 

• Encourage data curiosity and the use of data at scale. 

• Develop the practices to effectively and efficiently upskill engineers and grow our AI skillsets in the Poland office. 

• Represent Relativity at industry conferences, events, and with customers.  

  

Your skills: 

• An advanced degree in Computer Science, or a quantitative discipline AND 6 years of relevant industry experience 

• Excellent analytical skills 

• Data engineering experience – big data, ETL, data modelling 

• Solid knowledge of modern applied statistics 

• Understanding of machine learning algorithms 

• Experience with generative AI models and leveraging them as part of more complex systems to solve domain-specific tasks 

• Good programming (Python, preferably C#) skills and software engineering knowledge 

• Quick learner – our domain is on the bleeding edge of the AI boom 

• Proven track record of delivering and owning complex modelling solutions from inception to production maintenance 

• Intentional communicator – uses inclusive language whenever possible, communicates data science concepts to colleagues of all backgrounds, uses technical vocabulary judiciously and with intention. 

• Proficiency in English, including advanced oral and written communication and presentation skills 

• Knowledge of and adherence to the MLOps lifecycle 

• Experience in a Cloud environment with distributed teams and systems 

• Demonstrated ability to innovate and operate with a high level of autonomy 

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.  

#LI-MM5

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:

336 000 and 504 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.