About WithCoverage:

WithCoverage replaces the traditional insurance brokerage with AI-supercharged risk management designed for the modern economy. 

We partner with hundreds of high-growth, category-defining companies, including GoPuff, Eight Sleep, Bombas, Chomps, and Blank Street Coffee. Our clients span iconic consumer brands, hospitality leaders, GCs, advanced manufacturers, and next-generation defense contractors. They operate in complex risk environments and need a partner that can move at their speed.

Instead of a fragmented, manual brokerage stack, we have built a new category: elite risk advisors operating on top of proprietary technology. Our in-house Agency Management System gives our team and AI agents full visibility into policies, exposures, claims, billing, and commissions. This platform enables deep automation, better decisions, and a fundamentally higher standard of service.

WithCoverage was founded by JD Ross (co-founder of Opendoor) and Max Brenner (Bain, Compound). We have raised over $43M from leading investors including Sequoia, 8VC, Khosla Ventures and Crystal Venture Partners. We grew more than 10x last year while cash-flow positive, and we are very early in the opportunity.

Our ambition is not to build a better brokerage. It is to redefine how risk is managed across the economy.

Why Join Us

• Grow Faster – We're scaling quickly, giving you significant opportunities to learn, lead, and shape your career and the company's future.
• Work That Matters – We protect the world's most innovative brands: consumer icons, hospitality leaders, next-gen defense contractors, and US manufacturers.
• Be on the Frontier Edge of AI – Insurance is a $6 trillion global market—one of the largest, slowest-moving industries in the world—built on documents, communication, and expert judgment. Exactly the kind of domain where ML can create step-change improvements. You'll help prove what's possible when frontier AI meets real-world scale.

About the Role

We're looking for an ML Engineer to build the models and data systems that make our AI platform smarter over time. While our AI Agent Engineers focus on orchestrating LLMs into production workflows, you'll go deeper—building the custom models, evaluation systems, and data infrastructure that give our agents (and our business) capabilities that off-the-shelf models can't provide.

This is a high-ownership role. You'll work across the full ML lifecycle: identifying where custom models can outperform general-purpose LLMs, building the data pipelines to make that possible, and shipping models that run reliably in production. You'll turn the proprietary data we generate every day—across policies, claims, emails, and client interactions—into a compounding advantage.

We're not handing you a roadmap. The surface area for ML at WithCoverage is massive—and we've barely scratched it. We're looking for someone who can look at our data, our domain, and the state of the field—and move faster than the roadmap.

This role is based in our NYC office.

What You'll Do:

• Build Custom Models. Train and deploy models tailored to the insurance domain—document understanding, classification, extraction, risk prediction, and beyond. Identify where fine-tuned or purpose-built models can meaningfully outperform general-purpose LLMs, and build them.
• Own Data Infrastructure. Build the pipelines, labeling workflows, and data systems that make ML possible at scale. Turn messy, unstructured insurance data into clean, usable datasets. Design systems for continuous data collection and model improvement.
• Build Evaluation & Quality Systems. Design evaluation frameworks that measure model and agent performance with rigor. Build benchmarks, catch regressions, and create the feedback loops that let us iterate with confidence. Make quality measurable, not anecdotal.
• Embedded Problem Discovery. Dig into how our business actually works. Understand where predictions could replace guesswork, where classification could replace manual review, where ML could unlock capabilities we don't have today. Identify high-leverage opportunities that nobody has asked for yet. Prioritize ruthlessly. Build what matters most.

Who You Are:

• 3+ years building and deploying ML systems in production environments.
• Strong experience with NLP: transformers, embeddings, fine-tuning, text classification, information extraction.
• You've built ML pipelines end-to-end—data processing, training, evaluation, deployment, monitoring.
• Experience with embeddings, vector databases, and retrieval systems is a strong plus.
• Comfortable with Python and ML tooling (PyTorch, HuggingFace, etc.). Experience with our broader stack (Node.js, GraphQL, Postgres) is a plus.
• Strong fundamentals in software engineering: you write clean code, design sensible systems, and ship consistently.
• You think from first principles. You can navigate ambiguity, make tradeoff decisions, and figure out what to build when there's no playbook.
• You want ownership. You're excited by autonomy and accountability, not layers of process.

For candidates based in the United States, the expected pay range for this position at the start of employment is $180,000 – $275,000 /year. Actual compensation will be determined based on factors such as market location, job-related skills, experience, and qualifications. This role may also be eligible for additional variable compensation, including quota-based incentives where applicable. WithCoverage offers a comprehensive Total Rewards package for full-time employees, which includes equity grants and a robust suite of benefits.

What We Offer:

• Competitive compensation that may include equity
• Flexible paid time off
• Comprehensive benefit plans for medical, dental, vision, life, and disability
• Flexible Spending Accounts (FSAs): Health Care FSA and Dependent Care FSA 
• Commuter Savings Account
• Human Interest: 401(k) provider
• Time Off: Sick Leave, Family and Medical Leave, Flexible Time Off
• Paid Holidays: Observance of all major national holidays
• A curated in-office employee experience, designed to foster community, team connections, and innovation, that also includes catered lunches in the office on Fridays for in-office workers
• Collaborative, transparent, and fun culture