Machine Learning Engineer

Eve; San Francisco (CA); Hybrid; USD 195,000 - 350,000; Full time

Benefits offered by this job

Competitive Salary & Equity

401(k) Program with Employer Matching

Health, Dental, Vision and Life Insu r

Short Term and Long Term Disability

Commuter Benefits

Autonomous Work Environment

Workplace Setup Reimbursement

Telecomm Stipend

Flexible Time Off (FTO) + Holidays

Quarterly Team Gatherings

In office Perks

Job summary

Eve, a California-based legal AI company, is hiring a Machine Learning Engineer to scale the volume and complexity of our AI workflows from intake through resolution.

You will own the full ML stack, from data curation to deployment, building reliable systems with real users and high uptime in a fast-growing, equity-friendly environment.

Collaborate with product and legal experts to ship fast, shape the platform, and advance AI that helps plaintiff firms win more cases.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Applied ML/AI

Production ML systems

End-to-end ownership

AI reasoning

SOTA research interest

Analytical mindset

Job description

About Eve

Eve is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, recover more for clients, and grow with AI that works across every stage of a case, from intake through resolution. The next generation of great plaintiff firms will be AI-Native, and Eve is how they get there. But what makes Eve different isn't just the product. It's how we build it. If you're someone who takes ownership, stays curious, and wants to build AI that's already changing how law is practiced, this is where you belong.

Product-market fit: Eve is trusted by over 1000+ law firms, and we’re growing fast.
Backed by top investors: We’ve raised over $160M from world-class partners including Spark Capital, Andreessen Horowitz(A16z), Menlo Ventures, and Lightspeed.
Built by a world-class team: Engineers, designers, and operators from places like Scale, Meta, Airbnb, Cruise, Square, Rubrik, and Lyft are building Eve from the ground up.
AI-Native from day one: We’re on the bleeding edge of AI, collaborating directly with teams at OpenAI and Anthropic to build best-in-class AI workflows tailored for legal work.
Explosive growth: We are growing 2X revenue Quarter over Quarter.

About the Role

AI at Eve isn't a feature — it's the foundation. We're hiring a 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-mindful 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

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Eve and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location.

US Salary Range

$195,000 — $350,000 USD

Benefits

• Competitive Salary & Equity
• 401(k) Program with Employer Matching
• Health, Dental, Vision and Life Insurance
• Short Term and Long Term Disability
• Commuter Benefits
• Autonomous Work Environment
• Workplace Setup Reimbursement
• Telecomm Stipend
• Flexible Time Off (FTO) + Holidays
• Quarterly Team Gatherings
• In office Perks

* In office employees only

Disclaimer: For Contract Roles - The benefits and perks listed below are part of our standard company-wide overview and apply to full-time, salaried employees only. This is a contract position, and eligibility for the benefits listed (including 401(k) with employer match, Health/Dental/Vision/Life Insurance, Short/Long Term Disability, Flexible Time Off + Holidays, Commuter Benefits, and Equity) does not apply. Compensation for contract roles consists of the agreed hourly/contract rate, plus applicable reimbursements as outlined in your contractor agreement.

Eve Legal is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to your recruiter.

We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.