Application Engineer, Arize AI
$100-120k
+ Equity; salary dependant on transferable work experience, skill sets, and qualifications.
Machine learning observability platform
Open for applications
Machine learning observability platform
21-100 employees
Open for applications
$100-120k
+ Equity; salary dependant on transferable work experience, skill sets, and qualifications.
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- Recent CS graduate or professional with equivalent practical coding experience
- Solid foundation in Python, TypeScript/JavaScript, and modern software development practices
- Genuine passion for AI/ML technologies and their practical applications
- Strong written and verbal communication skills – you can explain complex technical concepts clea
What the job involves
- As a Solutions Engineer on the Open Source team, you'll be the critical bridge between Arize Phoenix and the community we serve. Your mission is to ensure users successfully adopt and implement Arize Phoenix across diverse AI use cases
- This hybrid role combines technical problem-solving with community engagement – one day you might build a demonstration app showcasing a new feature, the next you could be running a workshop at a tech conference or troubleshooting with users in our Slack community
- This is an ideal entry point for new computer science graduates or driven professionals transitioning into tech who have strong technical foundations and exceptional communication skills. You'll have a direct impact on product adoption while gaining invaluable experience across the AI ecosystem
- Community Support
- Community Support: Guide users through implementing tracing, experimentation, and evaluation tools for their LLM applications
- Solution Building
- Solution Building: Create example applications, demos, and documentation that showcase effective use of our platform
- Technical Outreach
- Technical Outreach: Represent Arize at events, run office hours, and engage with the AI developer community
- Product Advocacy: Collect user feedback, advocate for community needs, and help prioritize feature development
- Code Contribution: Develop improvements to our core libraries based on community interactions and needs
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
Insights
23% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Sep 2022
$38m
SERIES B
Sep 2021
$19m
SERIES A
Total funding: $61m
Company benefits
- Remote work opportunities
- Health, dental, & vision insurance
- 401K
- One Medical
- Rightway (healthcare navigation)
- Rula (mental health and wellbeing)
- SoFi (financial wellness)
- Open PTO policy
- WFH stipend
- Professional development stipend
- Coworking allowance
- Company wellness days
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
Berkeley, CA 94704
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.
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