DevOps Engineer, Arize AI
Machine learning observability platform
Job no longer available
Machine learning observability platform
21-100 employees
Job no longer available
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- 1-2+ years experience in site reliability engineering, DevOps, and system administration
- CS (preferred) or other technical degree, or equivalent practical experience
- Experience working with DevOps tools such as Kubernetes, Terraform, Ansible, Puppet and Chef
- Proficiency with scripting languages such as Python and bash
- Experience managing cloud infrastructure in AWS, GCP, and/or Azure
- Expertise in Linux administration, configuration, and networking protocols
Desirable
- Experience with on-prem deployment architectures
- Experience running a 24x7 SaaS platform with defined SLI, SLO, SLA
- Familiarity with operating machine learning & AI applications
What the job involves
- Work hands-on with the infrastructure that supports our distributed & highly scalable services in both SaaS and on-prem offerings
- Gather requirements from customers and adapt manifests and software to support new environments
- Use and augment monitoring tools to observe platform health, ensure performance and reliability
- Interact with the product team to test new features and package new on-prem releases
- Automate and optimize the release pipeline to make it as frictionless as possible
- Exhibit continuous curiosity for emerging technology that could solve our challenges
Otta's take
Sam Franklin
CEO of Otta
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.
Insights
Few candidates hear
back within 2 weeks
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
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
Founders
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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