At Relativity, we’re building a world-class Applied Science team to push the boundaries of intelligent systems in the legal domain, solving problems that matter in one of the most high-stakes domains out there, such as automating decision-making in document review, privilege detection, and case strategy.
Requirements
- 6–10+ years of professional experience in ML, Applied Science, or a closely related area.
- Experienced with a range of modeling techniques—from classic ML to large-scale generative models.
- Familiar with modern MLOps tooling (e.g., containers, workflow orchestration, telemetry, deployment patterns and experimentation).
- Strong Python Programmer, experienced in various data and machine learning libraries (e.g. numpy, pytorch, scikit-learn, pyspark)
- Comfortable reading and applying research; skeptical enough to validate the results.
- Proven ability to move fast without breaking everything: you know how to prototype—and how to simplify for production.
Responsibilities
- Write code that solves real customer problems and scales cleanly… Built to be easy to ship, operate, and maintain.
- Collaborate with fellow Applied Scientists… And with our Engineers, Product Managers, Designers, and Customers.
- Design and execute statistically sound experiments… Then automate them into reusable benchmarks.
- Rapidly build AI- and ML-powered prototypes… Then turn them into reliable, scalable production models.
- Select the right model for each task… Be it a decision tree or a frontier LLM.
- Stay grounded in evidence… And open to change.
Other
- Hold a Master’s or Ph.D. in a relevant field (e.g., Computer Science, Statistics, Applied Math) OR equivalent professional experience.
- Capable communicator, able to explain complex ideas to technical and non-technical stakeholders alike.
- Humble, curious, adaptable. Not afraid of failure. Not afraid to lead. Not afraid to ask questions.
- End-to-end owner – able to understand and learn about our problem space, devise solutions and bring them to market alongside our engineering, product and support organizations
- Must be able to work in a hybrid environment
