AI & ML Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

AI & ML Engineer New York, New York, New York City, New York, United States About Sandstone Sandstone is on a mission to elevate in-house legal from a support function into a true strategic partner. From day one, we've been clear about what we are-and are not. We are not replacing in-house legal teams. We are building a platform that amplifies them. Our platform enables modern legal teams to move at the speed of AI, deliver better outcomes, and create measurable business value. We unify legal data, power end-to-end workflows, and organize business context within the tools teams already use. Sandstone is the home for AI-native legal departments. Today, Sandstone is trusted by Fortune 500 companies and fast-growing innovators alike. We ship quickly, iterate relentlessly, and scale with intention. When you join Sandstone, you become part of a team that believes deeply in the compounding power of collaboration, rigorous problem-solving, and obsessive attention to detail. Our engineering team is elite, our lawyers ship code every day, and we are dedicated to building the most delightful product an in-house lawyer opens in the morning-and closes at the end of the day. The Role Sandstone is building the AI-native operating system for in-house legal teams. As an AI & ML Engineer, you will build the systems that make that possible: agents that reason over contracts and business context, retrieval systems that surface the right precedent, document understanding pipelines that turn legal work into structured intelligence, and evals that help us measure and

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