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Toast

Staff Machine Learning Engineer - Vision AI

Toast is hiring a Staff Machine Learning Engineer - Vision AI. Level rates it ; you can apply on Toast.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting allows some remote work.
  • Tools and skills the posting cites include Claude, Cursor and Claude Code.
  • Level lists 355 other open roles at Toast.
  • The role was posted in the last few days.

AI in this role

ClaudeCursorClaude Code

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.

Zone A$193,000—$309,000 USDZone B$168,000—$269,000 USDZone C$151,000—$242,000 USD

How Toast Uses AI in its Hiring Process

Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. We ask that you complete interviews and assessments on your own, without real-time AI tools, recording, or transcription bots, unless we tell you otherwise in advance. To learn more: https://careers.toasttab.com/ai-in-hiring

Our Approach to Hybrid Working

We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast

People Are the Secret Ingredient in Our Recipe for Success

At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry brings together people with a wide range of backgrounds, experiences, and perspectives, and we value that same breadth at Toast. We strive to build a culture grounded in authenticity, respect, and humility, where every Toaster has a real opportunity to grow, contribute, and do their best work—raising the bar in delivering exceptional experiences for our customers and each other.

Apply today!

Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com.

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For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

How we rate this

Staff Machine Learning Engineer - Vision AI at Toast rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ClaudeCursorClaude Code

Also common in machine learning engineer jobs at this level

Pay

Typical machine learning engineer job
$199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

  1. What's a project where you used Claude hands-on?
  2. Walk me through how you've used Cursor in your day-to-day work.
  3. What are the limits of Claude Code that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Claude, Cursor, and Claude Code. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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