OSS Infrastructure Engineer, Arize AI
$125-225k
+ Equity package
Machine learning observability platform
Be an early applicant
Machine learning observability platform
21-100 employees
Be an early applicant
$125-225k
+ Equity package
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- 3+ years of experience building scalable infrastructure and developer tools, ideally in an open-source context
- Strong understanding of the open-source development lifecycle and community dynamics
- Expertise in Kubernetes, Terraform, and other modern infrastructure tools
- Familiarity with build tools like Bazel and CI/CD systems
- A pragmatic approach to solving problems and prioritizing impactful solutions over trends
- Experience working with AI frameworks, LLM integrations, or observability platforms is a plus
- Familiarity with Go, Python, and some TypeScript is a Plus
What the job involves
- As an OSS Infrastructure Engineer, you will focus on designing, building, and scaling the open-source infrastructure that powers Arize Phoenix and its associated tools
- You’ll work directly with the CTO and open-source team to ensure the platform’s robustness, scalability, and accessibility for developers worldwide
- This is a unique opportunity to contribute to foundational infrastructure that will shape the way organizations observe and evaluate AI systems
- You’ll play a pivotal role in helping build a SaaS platform built on top of Phoenix
- We’re looking for an exceptional engineer with a passion for open source, a knack for scalable system design, and a commitment to delivering impactful solutions
- You’ll play a pivotal role in our engineering organization and within the broader community of Arize Phoenix users and contributors
- Collaborate with internal teams and the open-source community to architect and scale infrastructure that supports Arize Phoenix’s growth
- Enable and enhance Phoenix’s SaaS capabilities by building out features such as central authentication, data retention, and capacity scaling
- Build out a robust set of infrastructure tools and services that alleviates the operations of Arize's product offering
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
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
Company values
- Integrity - Do what you say, say what you do
- Balance - Hold space for what matters to you
- Candor - Be open, be honest, be constructive
- Humility - Keep a learning mindset
Company HQ
Mill Valley, CA
Articles
Leadership
Jason Lopatecki
(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
(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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