UX Designer, Arize AI
$100-165k
Plus a competitive equity package
Machine learning observability platform
Job no longer available
Machine learning observability platform
21-100 employees
Job no longer available
$100-165k
Plus a competitive equity package
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- You've made products noticeably better through interaction refinement (show us!)
- You understand design systems and animation libraries
- You've used feedback collection tools and incorporated user feedback into designs
- You can work in Figma to prototype
- You think about edge cases, loading states, and empty states automatically
- You've worked on complex tools (dev tools, data tools, B2B SaaS) where UX really matters
- You've built or contributed to design systems
What the job involves
- We're looking for a Designer Who Codes that obsesses over the details that make complex tools feel effortless
- You'll work on our LLM platform, creating functional features and refining them into intuitive, polished experiences
- Most engineering teams treat UX refinement as an afterthought squeezed between feature work
- We have a dedicated role for it because we believe the difference between "works" and "delightful" is what separates good products from great ones. You'll have the space to really care about craft
- Identify pain points
- Watch real users struggle in Fullstory, identify friction points, and fix them
- Prototype interaction alternatives rapidly (in Figma or code) to test different approaches
- Create, refine, and iterate on UX flows and interaction patterns
- Work closely with our Senior engineers who own feature architecture - they build the foundation, you perfect the interface
- Run lightweight usability tests to validate improvements
- Build reusable interaction patterns that the team can leverage
- A typical week might include:
- Watching 10 user sessions, identifying 3 common friction points
- Meeting with users to get deeper on new product features feedback
- Prototyping 2 different flows in Figma
- Implementing design improvements with smooth transitions and helpful inline guidance
- Pairing with Staff engineers to refactor a complex form into a multi-step wizard
- Running a quick usability test with 5 users on the new onboarding flow
Our take
Machine learning is rapidly becoming a fundamental and mainstream automation tool used across many industries. The issue, however, is that monitoring, assessing, and improving ML models is costly, and especially tricky without monitoring capabilities. It’s created a market demand for ML monitoring tools, and Arize’s platform offers a rich suite of them.
The Arize platform gives developers and operators comprehensive oversight of their models with tools including performance tracing, drift detection, and integration and deployment. This provides a crucial guardrail: as more decision-making is handed over to ML in areas like insurance and loans, poor ML model performance can have a catastrophic effect on both individuals and customers alike.
Remarkably, given this development, ML observability platforms aren’t yet in huge supply. Arize startup rivals like Censius and WhyLabs are making strong headway, but a clear winner has by no means yet emerged. Arize has, however, netted some major customers: Spotify, Instacart, Uber, and P&G are a handful of the major clients that will help it lay a strong foundation in what is anticipated to be a highly lucrative market.
Kirsty
Company Specialist at Welcome to the Jungle
Meet the team
Meet Andy, Product Design Team Lead
Our mission
Collaborate to create functional and innovative design solutions.Insights
23% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Feb 2025
$70m
SERIES C
Sep 2022
$38m
SERIES B
Total funding: $131m
Company benefits
- Remote work
- Open PTO policy
- Health, dental, vision insurance
- 401K
- Company wellness days
- Coworking
Company values
- Do > Say - We believe in building, not just talking. Execution matters more than meetings, and progress beats process. Instead of endless debate, we prototype. Instead of bureaucracy, we ship. AI moves fast—so do we.
- N+1 - Good enough isn’t good enough. We believe in continuous improvement—whether it’s improving AI-powered systems, our product, or ourselves, there’s always a better version to build, iterate, and level up.
- Bring Solutions - Spot a problem? Own it. We don’t waste time on complaints or excuses—we focus on fixing, improving, and building. Whether it’s a blocker in a project or a gap in how we work, the expectation is simple: push for a better way forward.
Company HQ
New York, NY 10006
Articles
Leadership
Jason Lopatecki
(Co-Founder & CEO)Previously a System Architect at Calix, before they moved on to found and serve as CSO/CIO at TubeMogul for over a decade.
Aparna Dhinakaran
(Co-Founder & CPO)Has held Software Engineer roles at both Dote and Apple, and worked on Machine Learning at TubeMogul and Uber. Also co-founded and served as CEO at Monitor ML, and is additionally a columnist at Forbes.
Share this job