Application Engineer, Arize AI

$100-120k

+ Equity; salary dependant on transferable work experience, skill sets, and qualifications.

TypeScript

JavaScript

Python

Entry and Junior level

New York

San Francisco Bay Area

Remote from US

Machine learning observability platform

Job no longer available

Meet the team

Machine learning observability platform

21-100 employees

B2BArtificial IntelligenceEnterpriseAnalyticsMachine LearningSaaSAutomation

Job no longer available

Meet the team

$100-120k

+ Equity; salary dependant on transferable work experience, skill sets, and qualifications.

TypeScript

JavaScript

Python

Entry and Junior level

New York

San Francisco Bay Area

Remote from US

21-100 employees

B2BArtificial IntelligenceEnterpriseAnalyticsMachine LearningSaaSAutomation

Company mission

To make the world’s AI work and work for the people.

Job

Company

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

Meet the team

Meet Andy, Product Design Team Lead

Our mission

Collaborate to create functional and innovative design solutions.

Insights

Led by a woman

Top investors

23% employee growth in 12 months

Glassdoor (4.9)

Company

Funding (last 2 of 3 rounds)

Sep 2022

$38m

SERIES B

Sep 2021

$19m

SERIES A

Total funding: $61m

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

Arize AI hopes it has first-mover advantage in AI observability

Enterprises Onboard AI Teammates Faster With NVIDIA NeMo Tools to Scale Employee Productivity

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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