Machine Learning Sales Engineer

The Opportunity

AI is rapidly changing the world. From processing job applications and credit decisions, to making content recommendations and helping researchers analyze genetic markers at scale -- many aspects of our daily lives are touched by machine learned systems in some way. 

Arize is the leading machine learning observability platform to help ML teams discover issues, diagnose problems, and improve the results of machine learning models. In short: we are here to build world class software that helps make AI work better.  

The Team

Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. We are looking for a Sales Engineer to join the good fight and get this product in the hands of every Machine Learning organization.

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 a 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.

What You’ll Do

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

What We’re Looking For

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 …