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You will build and optimize data pipelines to enrich legal documents and develop systems for large-scale web scraping. Additionally, you will expose data services through APIs and design benchmarks to evaluate core legal research tasks.
Join a small legal technology team building data infrastructure and AI-powered services for legal research. You will help make a broad collection of U.S. case law more accurate, reliable, and accessible to software products and data customers.
Build data pipelines that enrich legal documents with relationships such as appeals, remands, consolidations, and decisions that overrule prior cases.
Develop systems to monitor and improve the reliability and accuracy of large-scale web scraping.
Optimize and evaluate core tools for citation extraction and resolution, and for determining relationships among courts.
Expose data services through APIs, MCPs, and WebSockets.
Design benchmarks and evaluations for core tasks using human and synthetic assessments.
At least two years of experience as a backend technical generalist, ideally in a startup environment, with strong engineering fundamentals and meaningful ownership of systems or greenfield projects.
Proficiency in Python and SQL, along with the ability to build and deploy projects end to end on your preferred infrastructure.
Basic to intermediate infrastructure and DevOps experience.
Hands-on software engineering experience, including a sustained move from research or academia into building production software where applicable.
Interest or experience in statistics, machine learning, or AI, and familiarity with modern AI tools.
Full-stack experience and personal software projects are a plus.
Base salary: $170,000 to $240,000 annually. Visa sponsorship is not available; candidates must be authorized to work without sponsorship.
Remote within the United States. Primary location: New York, New York.
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