Senior Software Engineer, Vision AI
Toast · Remote, US
About this role
**Toast — Senior Software Engineer, Vision AI** ## About the role Toast powers restaurants of every size, and we’re investing in **Vision AI** to help operators see more of what’s happening in their restaurants—so they can run more efficiently, provide better service, and become more profitable. As a **Senior Software Engineer, Vision AI**, you’ll build major parts of the system **end to end**, from services that process video to the customer-facing features operators use every day. You’ll have real influence on how Vision AI is built. ## Responsibilities - **Build full-stack, customer-facing features**: Design and build vision-powered experiences for restaurant operators across Toast products (backend APIs to UI). - **Own major platform components**: Build and own key parts of the platform (e.g., video pipeline and services that process/analyze footage) with an emphasis on security, reliability, and extensibility. - **Integrate vision models into products**: Partner with ML engineers to bring vision/AI models into production, including evaluation and monitoring. - **Contribute to architecture and design**: Help shape technical decisions—building for today while keeping a clear path forward. - **Collaborate across teams**: Work with product, design, and engineering partners on integrations and dependencies. - **Work AI-forward**: Use AI coding tools and agent harnesses as a core part of how you design, build, test, and ship. - **Raise the bar**: Set high standards for quality, testing, reliability, security, and privacy; support team growth through code reviews and collaboration. ## Requirements - **5+ years** building and shipping production software, including customer-facing products. - **Full-stack skills**: Strong backend experience with cloud infrastructure (**AWS preferred**), event-driven systems (e.g., **Pulsar/Kafka**), storage, and APIs; experience with **Kotlin/Java or similar** plus web front-end experience. - **Comfort with AI and models**: Experience integrating AI/ML (including LLM or vision-language model APIs) into production; curiosity to go deeper with ML engineers. - **Pragmatic engineering**: Build the simplest solution that solves the problem well—without over-engineering. - **Zero-to-one experience**: Take ambiguous ideas from prototype to production with real customers. - **AI-forward ways of working**: Daily use of AI coding assistants/agent harnesses (e.g., **Claude Code, Cursor**). - **Collaboration & communication**: Work closely with product/design/engineering and clearly explain tradeoffs. ## Not a fit if… - You only want to work on one layer of the stack. - You’re more attached to the solution than the problem. - You build for scale before it’s needed. - You prefer established processes/tooling (this team shapes its own ways of working). - You’re uncomfortable with ambiguity. - You’d rather be perfect than experiment (they test with real restaurants and iterate). - AI-assisted development isn’t part of how you work. ## Special Sauce (Nice to Haves) - React + TypeScript web front-end experience - Computer vision, video analytics, or camera-based product experience - Video experience (streams/codecs/tools like **ffmpeg**) and real-time video pipelines - ML systems experience (inference pipelines, evaluation, model monitoring) - Connected device fleet experience (provisioning/auth, remote updates, constrained networks) - Data-rich product experience (dashboards, analytics, alerts) - Privacy-sensitive s
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