Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI.
With a world-class team, we're unlocking the next era of autonomous
transportation with technology that's powering commercial autonomous trucks and
robotaxis. Waabi is backed by and partners with world leaders in AI, automotive,
logistics, and deep tech.
With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing
quickly and looking for diverse, innovative and collaborative candidates who
want to impact the world in a positive way. To learn more visit: www.waabi.ai
[http://www.waabi.ai]
We're seeking a Senior Product Designer to own the human-in-the-loop workflows
at the core of how Waabi turns raw driving data into a safer autonomy stack: the
software environments where expert human judgment and automation work as one to
make every engineer, analyst, operator, and researcher faster.
These are the workflows where a human expert and an automated system have to
move together: data labeling, map annotation, track testing, and release
testing. Your job is to design the environments that make that collaboration
fast and high-signal, and then bring shared patterns into the design system for
compounding returns across every internal and partner-facing surface.
You'll join as the third product designer at Waabi, sitting on the Product,
Design & TPM team. You'll be the systems-minded builder who turns one-off UI
work into compounding returns across the whole platform.
You will…
* Design data labeling and annotation workflows. You'll design the tools for
data curation, internal lightweight labeling, QA, and the feedback loops that
connect label quality to model performance. Today this work lives in many
surfaces, and your goal will be to unify the workflows to accelerate training
data throughput and quality, to continually improve autonomy safety at scale.
* Design data discovery surfaces and annotation tools. Grow the primary tools
for finding, filtering, and curating AV data across logs, events,
simulations, and labels. You'll help design the experience that lets triage
analysts, systems engineers, autonomy engineers, and ML researchers navigate
petabytes of driving and simulated data. You'll also own the design for our
map annotation tooling: task management, branch/merge workflows, annotator
feedback loops, defect logging, and urban surface street annotation as Waabi
expands from highway trucking to urban robotaxi deployments.
* Ground the work in research. Get out of the tools and into the workflows.
Shadow labelers, annotators, triage analysts, and right-seaters in their real
environment. Produce qualitative and quantitative insight on where time and
signal are lost, and disseminate it so the whole team designs from the same
picture of the user.
* Build and scale Waabi's design system. Work with designers and full-stack
engineers to take our nascent system and turn it into a robust, branded
component system. This means complex, reusable components: timeline
scrubbers, rich multi-select filters, pass/fail summary cards, map
visualization primitives, data tables with inline actions. These components
serve triage, metrics dashboards, data exploration, mapping, fleet ops, and
partner-facing UI.
* Establish front-end and design infrastructure for tooling self-service. Build
the context architecture that lets teams build their own UI with UX best
practices baked in. Enable robust prototyping with read-only or snapshot data
so teams can iterate without touching production.
* Ship directly in code. You'll contribute to production React codebases using
AI-assisted tools. The shipped product is the deliverable, not a Figma
handoff.
Qualifications
* Data-centric workflow designer who builds in code. 5-8+ years designing
complex, data-rich tools where the primary interface is structured data:
tables, filters, search, dashboards, maps, or annotation tools. You see the
cross-tool workflow as your unit of work, not the single screen. You can make
dense information scannable and actionable without dumbing it down, and you
validate by building working prototypes on real data, not static mocks.
* Design-system builder. You think in components, tokens, patterns, and
infrastructure, and see the reusable primitive inside every one-off request.
You've built or significantly grown a design system, and you understand the
difference between a component library and a design system: tokens,
documentation, governance, adoption, and the political work of supporting
engineers to use it.
* AI-native builder. You use AI-assisted coding (Cursor, Claude Code, or a
similar agentic setup) as a default part of how you prototype and ship, not a
novelty. It's how you get from idea to working software fast.
* First-principles thinker. You strip problems down to their fundamentals. The
tools you'll design have no off-the-shelf pattern to copy. Curation
workflows, map annotation, track test playlist management, data lineage
visualization: these require you to understand the domain deeply and invent
the right interaction model.
* Strong front-end intuition. You don't need to be a senior React engineer, but
you understand component architecture, state management, and the constraints
of web-based data visualization well enough to design things that are
buildable and performant.
* Infrastructure mindset. You're energized by the meta-problem: how do we make
everyone faster? You see AGENTS.md files, context documentation, and
component APIs as design deliverables, not overhead.
BONUS / NICE TO HAVE
* Advanced AI-assisted workflows. Custom agentic setups, and real opinions
about how AI changes the relationship between design systems and self-service
UI.
* GIS or mapping tools background. Experience with map annotation, geospatial
data, or tools like Mapbox, QGIS, or proprietary mapping tools.
* Data platform or ML tooling experience. Prior work designing labeling tools,
data curation interfaces, dataset management, or ML experiment tracking.
* Design system at scale. You've maintained a system used by 10+ engineers
across multiple product surfaces and dealt with the versioning, adoption, and
governance challenges that come with it.
* AV, robotics, or safety-critical domains. Prior experience where the quality
of tooling directly impacts physical safety.
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The US yearly salary range for this role is: $100,300 - $200,000 USD in addition
to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are
determined based on several factors in accordance with the Company’s
compensation practices. The salary base range is reflective of the minimum and
maximum target for new hire salaries for the position across all US locations.
Note: The Company provides additional compensation for employees in this role,
including equity incentive awards and an annual performance bonus.
Perks/Benefits:
* Competitive compensation and equity awards.
* Health and Wellness benefits encompassing Medical, Dental and Vision coverage
(for full-time employees only).
* Unlimited Vacation.
* Flexible hours and Work from Home support.
* Daily drinks, snacks and catered meals (when in office).
* Regularly scheduled team building activities and social events both on-site,
off-site & virtually.
* As we grow, this list continues to evolve!
Waabi is a technology start-up building technologies to transform the way the
world moves. Join our talented team to be a part of the future and to make an
impact!
Waabi is an equal opportunity employer. We celebrate diversity and are committed
to creating a supportive, inclusive, and accessible workplace for all our
employees. We seek applicants of all backgrounds and identities, across race,
color, ethnicity, national origin or ancestry, age, citizenship, religion, sex,
sexual orientation, gender identity or expression, military or veteran status,
marital status, pregnancy or parental status, caregiver status, disability, or
any other characteristic protected by law. We make workplace accommodations for
qualified individuals with disabilities as required by applicable law. If
reasonable accommodation is needed to participate in the job application or
interview process please let our recruiting team know.