Senior AI Product Engineer, Arize AI
Fullstack
$125-225k
+ Equity
More information about location
Machine learning observability platform
Open for applications
Machine learning observability platform
21-100 employees
Open for applications
$125-225k
+ Equity
More information about location
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- 5+ years of frontend experience working on external user-facing UI’s - preferably in React and Typescript
- Previous experience debugging complex systems in a team environment
- Enthusiasm and interest in the AI and LLM ecosystem, with a desire to learn and stay updated on emerging technologies
- Previous work building and operating highly complex, high-volume SaaS platforms/systems
- Strong sense of product ownership in order to push features over the line
- Passion for creating beautiful UX design with the end user in mind
- A good teammate, someone who sees supporting their team as a core part of the job
Desirable
- Experience working with GraphQl or a comparable API technology
- Experience working with ML, analytics, data science or data visualization products
- Working knowledge of Machine Learning and/or Data Science
- First-hand experience working with large language models (LLMs) or developing AI products
What the job involves
- Our Fullstack Engineering team builds both the highly scalable distributed services that power Arize's ML observability platform and the intuitive frontend applications that bring these capabilities to life
- We focus on delivering robust features that help clients interpret, visualize, and monitor their AI and ML models across the entire stack
- You will be a part of the core team that drives product innovation at Arize
- You will be challenged with understanding how some of the most impactful engineering teams are developing AI and LLM-powered applications, and how to build the right tools to enable them to do their best work
- Our product solutions range from clean APIs that magically instrument applications, interactive playgrounds for prompt engineering and agent development, or scaling up real-time evaluation infrastructure to handle millions of annotations per second
- Write maintainable, scalable, and performant code across the stack primarily in Typescript and React with opportunities to work in Python and Go
- Design and build APIs, and domain / object models specific to our customers’ Machine Learning and LLM workflows
- Design and build out performant and reusable react components that will be used throughout the application
- Research and implement cutting-edge visualization & dimensionality reduction algorithms in a distributed environment
- Collaborate with our product, design, and directly with customer engineering teams to enhance and expand our product offerings
- Contribute to the build our own in-house AI Agents
- Participate in or lead architectural decisions for new and existing features in collaboration with product, design and our backend teams
- Contribute to design & code reviews and technical documentation
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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