AI Sales Engineer, Arize AI
$140-230k
Machine learning observability platform
Job no longer available
Machine learning observability platform
21-100 employees
Job no longer available
$140-230k
21-100 employees
Company mission
To make the world’s AI work and work for the people.
Role
Who you are
- Strong Communication Skills:
- You can empathize with the frame of reference of who you are communicating with and tailor your message and approach accordingly
- Ability to simplify complex, technical concepts
- A quick and self learner:
- You are undaunted by the technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV
- You ask the right questions with the customer to uncover nuances in their unique deployments
- Ability to work within ambiguity and take action with limited direction
- Knowledgeable in Machine Learning:
- You may not have a PhD in ML but you know the difference between Linear Regression and Boosted Trees and the advantages / disadvantages of each
- You have some experience training models in common packages such as scikit-learn, HuggingFace, fastai, and etc
- 5+ years within customer facing role:
- Pre-sales, technical account management, or consulting experience
- Worked with customers within the high enterprise (e.g. Fortune 500, etc)
- Proficiency in:
- Python
- Linux/Unix
- Bonus Points, But Not Required
- Previous experience working across and aligning Sales, Product, and Engineering
- Previous experience within a team that underwent a high growth stage
- Previous engineering experience in: Data Engineering, MLOps, Kubernetes, GCP / AWS / Azure
What the job involves
- You'll work side-by-side with our Account Executives to articulate the Arize value and overall strategy to differentiate the platform throughout the sales process and drive POCs from requirements gathering to close
- The activities performed by an AI Sales Engineer are diverse - one day you might be assisting with a high-level pitch of Arize to a CDO, and the next day you might be working hands-on to develop a small proof of concept
- You are the trusted advisor to the customer:
- Build relationships with technical stakeholders
- Lead product demonstrations of the Arize platform
- Lead discovery to understand prospect’s ML stack to collaborate with the Sales team to construct a compelling value proposition of the Arize Platform
- Handle technical objections and develop strategies across sales, engineering, and product to unblock them
- Act as a Domain Expert within AI/ML:
- Write educational and compelling blog posts about ML and MLOps related topics
- Collaborate to create and enhance documentation, recorded video assets and other publically available as well as internal enablement materials
- Engage in relevant ML communities online to raise awareness on challenges of deploying ML in production
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
Meet the team
Meet Andy, Product Design Team Lead
Our mission
Collaborate to create functional and innovative design solutions.Insights
23% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Feb 2025
$70m
SERIES C
Sep 2022
$38m
SERIES B
Total funding: $131m
Company benefits
- Remote work
- Open PTO policy
- Health, dental, vision insurance
- 401K
- Company wellness days
- Coworking
Company values
- Do > Say - We believe in building, not just talking. Execution matters more than meetings, and progress beats process. Instead of endless debate, we prototype. Instead of bureaucracy, we ship. AI moves fast—so do we.
- N+1 - Good enough isn’t good enough. We believe in continuous improvement—whether it’s improving AI-powered systems, our product, or ourselves, there’s always a better version to build, iterate, and level up.
- Bring Solutions - Spot a problem? Own it. We don’t waste time on complaints or excuses—we focus on fixing, improving, and building. Whether it’s a blocker in a project or a gap in how we work, the expectation is simple: push for a better way forward.
Company HQ
New York, NY 10006
Articles
Leadership
Jason Lopatecki
(Co-Founder & 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
(Co-Founder & 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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