Senior Computer Vision Deep Learning scientist

At Honeycomb, we're not just building technology , we're reshaping the future of insurance.

In 2025, Honeycomb was ranked by Newsweek as one of "America's Greatest Startup Workplaces," and Calcalist named it as a "Top 50 Israel startup."

How did we earn these honors?

Honeycomb is a rapidly growing global startup, generously backed by top-tier investors and powered by an exceptional team of thinkers, builders, and problem-solvers. Dual-headquartered in Chicago and Tel Aviv (R&D center), and with 5 offices across the U.S., we are reinventing the commercial real estate insurance industry, an industry long overdue for disruption. Just as importantly, we ensure every employee feels deeply connected to our mission and one another.

With over $55B in insured assets, Honeycomb operates across 18 major states, covering 60% of the U.S. population and increasing its coverage.

If you're looking for a place where innovation is celebrated, culture actually means something, and smart people challenge you to be better every day - Honeycomb might be exactly what you've been looking for.

About the Role

We are looking for a Senior Computer Vision / Deep Learning Scientist to join Honeycomb's automated decision systems group as part of the Visual Assessment Team.

What You'll Do

Build and deploy end-to-end deep learning computer vision models for real-world insurance use cases.
Work hands-on with state-of-the-art vision models, VLMs, and large multimodal models.
Extract high-quality visual and multimodal features that improve automation and decision quality in risk assessment.
Improve model robustness and accuracy across diverse, real-world image distributions.
Partner with product, engineering, and data teams to deliver scalable ML solutions.
Lead experimentation, training strategies, retraining, and performance evaluation.
Use modern AI tools (e.g., Claude Code, Notion) to accelerate development and collaboration.
Contribute to shared ML standards, code quality, and technical reviews.

Requirements

MSc in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or a related field from a leading institution. - PhD an advantage
5+ years of experience in computer vision and deep learning.
Proven ability to build end-to-end deep learning models and deliver them to production.
Strong Python skills and experience with modern deep learning frameworks.
Hands-on experience with data pipelines, including data collection, organization, and labeling.
Experience working in collaborative, Git-based development teams.
Ownership mindset, strong communication skills, and ability to work independently
Familiarity with production ML monitoring and reliability.
Experience with Vision-Language Models or large multimodal models. - an advantage

Why Honeycomb

Build foundational visual AI for automated underwriting and risk assessment.
Work on high-impact, real-world problems with fast paths to production.
High ownership, minimal bureaucracy, and close collaboration with leadership.
Operate in a modern AI-native environment using tools like Claude Code and Notion.
Influence technical direction in a fast-moving, mission-driven company.