Senior Manager, Applied Science

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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 Manager, Applied Science – Poland Office AI Role Relativity already has a large Engineering team in our Poland office; the team currently is focused on other parts of Relativity’s broad technology offering. The Senior Manager, Applied Science – Poland Office will work with other AI leaders across Relativity to grow our AI-focused talent pool in Poland, encourage cross functional learning and innovation in the Poland office, lead major initiatives within our AI strategy, and own key functions and a new Applied Science team within our AI strategy. Our goal is to accelerate our AI innovation with the additional talent and scale of our Poland office.

Responsibilities:

• Represent Relativity’s AI strategy, key product efforts, and teams/functions in Poland.
• Represent Relativity at industry conferences, events, and with customers.
• Working with other AI leaders, recruit and build a cross functional AI team (data engineering, applied science, feature development) via industry talks and posts, candidate outreach, networking, and partnerships.
• Lead large initiatives from an investment perspective via clear prioritization, thoughtful resource allocation, sweating the details, and great communication to inspire the team.
• Lead collaboration with our engineering teams, applied scientists, and product managers to bring ideas from proof of concept to scaled solution.
• Prioritize technical investments roadmap and help prioritize tech debt and architecture investments.
• Mentor talent within the AI engineering team to promote career development, risk taking, innovation, and create a culture of learning.
• Inspire others with a compelling vision and a plan of how AI technology can transform Relativity.
• Encourage innovation and data curiosity and the use of data at scale.
• Working with other AI leaders, evolve our AI operating model to be multi-office and global in reach.
• Own key features, technology functions, and teams within the AI strategy; this ownership will evolve over time as the Poland team grows.
• Develop the practices to effectively and efficiently onboard engineers and grow our AI skillsets in the Poland office.

Minimum Qualifications:

• Experience building and leading applied science teams.
• Excellent communication skills.
• Experience in mathematical and statistical modeling.
• Experience with privacy standards such as GDPR and CCPA.
• Proven leadership skills and track record of delivering complex modeling solutions.
• Experience collaborating with engineering teams with conceptual knowledge on data engineering project lifecycles and techniques.
• Experience running systems in either AWS, Google Cloud, or Azure.

Preferred Qualifications:

• Experience in modern programming languages and compute environments in cloud environments.
• Experience leveraging data for knowledge retrieval, search, and ML/AI based solutions in production environments for mission critical use cases.
• Experience in a SaaS/Cloud environment with distributed teams and systems.
• Experience launching new product

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