DevOps Engineer, Arize AI

Salary not provided

AWS

Kubernetes

GCP

Python

Java

Bash

Linux

Postgres

Terraform

Ansible

Azure

Puppet

Chef

Bazel

Junior and Mid level

Remote in US

Machine learning observability platform

Job no longer available

Machine learning observability platform

21-100 employees

B2BArtificial IntelligenceEnterpriseAnalyticsMachine LearningSaaSAutomation

Job no longer available

Salary not provided

AWS

Kubernetes

GCP

Python

Java

Bash

Linux

Postgres

Terraform

Ansible

Azure

Puppet

Chef

Bazel

Junior and Mid level

Remote in 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

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

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

Led by a woman

Top investors

Few candidates hear
back within 2 weeks

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 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

Arize AI Raises $38 Million Series B To Scale Machine Learning Observability Platform

Arize AI goes self-service with ML observability platform

Beyond Monitoring: The Rise of ML Observability

Arize AI Introduces AI Copilot

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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