Machine Learning Engineer

AI at Eve isn't a feature — it's the foundation. We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work — from intake through resolution — we need engineers who can push our models and agent systems to be faster, smarter, and more reliable.

You'll own the full stack of applied ML — from data curation to evaluation and production deployment — building systems that handle the kind of complex, high-stakes reasoning that most AI products never have to touch. Working closely with product and legal experts, you'll ship fast, drive projects end-to-end, and help shape both the platform and the future of legal AI.

What You'll Do:

You'll build and improve ML systems that operate in real-world conditions, where reliability, accuracy, and domain nuance matter. At Eve, you will:

Build AI systems that understand, analyze, and reason across complex legal tasks and queries

Elevate AI Reasoning: Architect and refine the reasoning capabilities of our models to drive complex, high-stakes decision-making within the legal domain

Treat model quality as a first-class ML optimization problem, using real usage data to make our systems more reliable, adaptable, and resilient

Build rigorous evaluation frameworks that measure AI performance and ensure meaningful, trustworthy outcomes in a high-stakes legal context

Collaborate Cross-Functionally: Work closely with product engineers to integrate models into user-facing features, and partner with legal professionals to translate domain expertise into technical requirements

What We're Looking For:

You're a product-minded Machine Learning Engineer who enjoys building real systems people depend on. You'll likely have:

4+ years of engineering experience, with a focus on applied ML/AI products

Proven track record of shipping ML systems in production, with real users and high uptime

Experience developing advanced AI systems, particularly those that deconstruct complex tasks into manageable steps

Strong analytical sense: you build frameworks to measure the metrics that matter and iterate quickly from real usage

Ownership mindset: you drive projects end-to-end and thrive on problems that don't have clean answers yet

Enjoy following SOTA research into new models and agent architectures.