Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. Toast powers restaurants of every size, from neighborhood favorites to the largest multi-unit brands in the industry. We're investing in Vision AI to help operators see more of what's happening in their restaurants and act on it, so they can run more efficiently, provide better service, and become even more profitable.

We're looking for a Staff Machine Learning Engineer, Vision AI to build the platform and the products that bring it to restaurant operators. You'll own major parts of the system end to end, from the services that process video to the customer-facing features operators use every day, and you'll have real influence on how Vision AI is built.

A day in the life (Responsibilities)

Build ML systems and drive model choices. Select and integrate vision models, including vision-language models, and build the ML systems around them, such as inference pipelines, evaluation, and monitoring of model performance in production.
Contribute to architecture and design. Help shape technical decisions with the team, building what's right for today while keeping a clear path to where we're headed.
Collaborate across teams. Partner with product, design, and teams across Toast on integrations and dependencies when the work calls for it.
Work AI-forward. Use AI coding tools and agent harnesses as a core part of how you design, build, test, and ship, and share workflows that make the team faster.
Raise the bar. Set a high standard for quality, testing, reliability, security, and privacy in the areas you own, and help other engineers grow through code reviews and collaboration.

What you'll need to thrive (Requirements)

Solid engineering experience. 8+ years building and shipping models in production.
Mastery of a modern backend language such as Python, Java, Kotlin, Go, or Scala.
Comfort with AI and models. Experience integrating AI or ML models, or LLM and vision-language model APIs, into production features.
Strong understanding of data modeling, query languages, and the online/offline data patterns that underpin ML systems.
Deep proficiency with distributed systems concepts: consistency, latency, throughput, fault tolerance, and observability.
Pragmatic engineering. You build the simplest solution that solves the problem well, without over-engineering, and know when to invest in more.
Zero-to-one experience. Experience taking ambiguous ideas from prototype to production with real customers.
AI-forward ways of working. Daily use of AI coding assistants and agent harnesses (e.g. Claude Code, Cursor).
Collaboration and communication. Ability to work closely with product, design, and engineering partners and explain tradeoffs clearly.
Bachelor's degree in Computer Science or a related field, or equivalent practical experience

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy.