Senior Backend 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
- 5+ years of experience working with high performant backend systems
- Strong experience writing Go, Python, Java, or similar server programming languages
- Strong experience writing concurrent and distributed programs
- Knowledge working with public clouds & container orchestration - AWS, GCP, Azure, Kubernetes, etc
- Experience building and operating highly complex SaaS platforms / systems
- Proven experience leading and/or significantly contributing to end-to-end large scale projects
Desirable
- Prior experience working in a start up enviornment
- Working knowledge of Machine Learning and/or Data Science
What the job involves
- Write maintainable, scalable performant Go
- Build high volume and highly available analytics systems
- Design and build APIs specific to our customers’ ML workflows
- Prototype, optimize, and maintain scalable backend services that power Arize core platform
- Extend, and contribute back to, open source OLAP databases and distributed message queue frameworks
- Research and implement cutting edge visualization & dimensionality reduction algorithms in a distributed environment
- Provide guidance and mentorship to other engineers on the team while also leading projects end-to-end
- Partner with our design, product, and fullstack teams in order to enhance and expand our product roadmap
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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