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Toast

Principal Machine Learning Engineer, Vision AI

Toast is hiring a Principal 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
computer-vision

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 Principal Machine Learning Engineer, Vision AI to architect and build the platform behind these products. You'll have an outsized influence on how Vision AI is built and how it reaches restaurants across Toast. This is a highly hands-on role: you'll spend most of your time designing, building, and shipping, and you'll own the technical direction of the platform.

A day in the life (Responsibilities)

  • Architect and build the core platform. Design the video pipeline and other essential components, from how video is captured and ingested to how it's stored, processed, and delivered, so the platform is secure and reliable.
  • Own the services that analyze video. Build the services that process footage, run vision models, and turn what they see into observations and metrics restaurants can act on.
  • 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. Partner with our ML engineers as models mature.
  • Build customer-facing use cases across Toast. Bring vision-powered features to restaurant operators across Toast's products and surfaces.
  • Set the technical direction. Make the key architecture decisions for the Vision AI platform, building what's right for today while keeping a clear path to where we're headed.
  • Stay hands-on. Write production code, prototype new ideas, and ship. You'll lead through building, not just reviewing.
  • Collaborate across orgs. Partner with teams across Toast on integrations, dependencies, and working models when the work calls for it.
  • Lead with AI-forward engineering. Use AI coding tools and agent harnesses as a core part of how you design, build, test, and ship, and help the team adopt workflows that make everyone faster.
  • Raise the bar. Mentor engineers, set standards for reliability, security, and privacy, and make the platform easier to build on with every use case.

What you'll need to thrive (Requirements)

  • Deep engineering experience. 10+ years building software, including designing and shipping distributed systems and data pipelines in production at scale.
  • Backend and cloud expertise. Strong experience with cloud infrastructure (AWS preferred), event-driven systems (e.g. Pulsar or Kafka), storage, and APIs, in Kotlin, Java, or similar languages, plus comfort with Python.
  • Experience with ML systems and video. You don't need to be a model researcher, but you understand how models are trained, tuned, and served, and you've built and operated ML systems in production, including inference pipelines, evaluation, and model monitoring. You're also comfortable working with video (streams, codecs, tools like ffmpeg).
  • Pragmatic architecture. A track record of designing systems that fit the current stage, avoiding over-engineering while leaving room to grow.
  • Zero-to-one experience. Experience taking ambiguous ideas from prototype to production with real customers.
  • Hands-on keyboard. You still write significant production code and enjoy doing it.
  • AI-forward ways of working. Daily use of AI coding assistants and agent harnesses (e.g. Claude Code, Cursor), and experience building with LLM or vision-language model APIs.
  • Collaboration and communication. Ability to align engineers, product partners, and other orgs around technical decisions and explain tradeoffs clearly.

This role may not be a fit for you if...

  • You want a primarily cross-org or architecture-only role. This is a hands-on keyboard role. You'll spend most of your time building, with cross-org collaboration when the work requires it.
  • You're more attached to the solution than the problem. We want someone obsessed with solving real problems for restaurant operators, who picks the simplest approach that solves them.
  • You tend to build for scale before it's needed. We need someone who builds the right solution for where we are today and what customers are telling us, while keeping long-term direction in mind and knowing when to invest in it.
  • You prefer established processes and tooling. This team moves fast and shapes its own ways of working. You'll help create the workflows, tools, and standards rather than inherit them.
  • You're uncomfortable with ambiguity. The problems we take on and the best ways to solve them will keep evolving, and priorities will shift as we learn from customers.
  • You'd rather be perfect than experiment. We move fast, test ideas with real restaurants, and accept that some of what we build will be thrown away once we learn what works.
  • AI-assisted development isn't part of how you work. We expect AI tools to be central to how we design, build, and ship.

Special Sauce (Nice to Haves)

  • Experience building computer vision, video analytics, or camera-based products.
  • Experience with real-time video pipelines and streaming (e.g. Amazon Kinesis Video Streams, GStreamer, WebRTC).
  • Experience with connected device fleets: device provisioning and authentication, remote updates, and constrained networks.
  • Experience building privacy-sensitive systems that handle video or personal data.
  • Background in restaurant, retail, hospitality, drive-thru, or other operationally complex environments.

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.

#LI-REMOTE

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$230,000—$368,000 USDZone B$200,000—$320,000 USDZone C$180,000—$288,000 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

Principal Machine Learning Engineer, Vision AI at Toast rates 89 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

Computer visionClaudeCursorClaude 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. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. Walk me through how you've used Claude in your day-to-day work.
  3. What are the limits of Cursor that you've run into, and how did you work around them?
  4. What's a project where you used Claude Code hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Computer vision, 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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