ML 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.

As we continue to innovate and develop our products, you will have the opportunity to solve a wide variety of problems and situations. On a typical day, you may go from debugging a subtle issue in an open source dependency to hopping on a call with a customer to understand their workflow. All without missing a beat. 

If you are an engineer who wants to work in a high velocity, no ego environment -- this is the place for you! If you are someone who wants to have total ownership over your work and be challenged to take yourself to the next level -- we want to talk to you!

What You’ll Do

• Own the customer relationship, from the initial problem-solution to post-sales growth

• Lead product demonstrations of the Arize platform

• Learn and develop a deep understanding of the customer’s ML stack and business needs and how Arize’s platform can deliver value for them. 

• Handle technical objections and develop strategies across sales, engineering, and product to unblock them. 

• Own creation and distribution of technical content in partnership with the Community team

• Write educational and compelling blog posts about ML and MLOps related topics

• Produce demos, video tutorials, and other resources addressing varying customer use cases

• Engage in relevant ML communities online to raise awareness on challenges of deploying ML in production

What We’re Looking For

• Excellent communication, presentation, and writing skills 

• You can empathize with the frame of reference of who you are communicating with and tailor your message and approach accordingly. 

• You can write about highly technical topics in an engaging manner.

• 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.

• 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.

• Proficiency in

• Python

• Linux/Unix

Bonus Points, But Not Required

• Previous engineering experience in

• Data Engineering

• MLOps

• Kubernetes

• GCP / AWS / Azure

• Previous experience teaching in any capacity, preferably in technical topics.

• Previous experience working across and aligning Sales, Product, and Engineering

More About Arize

Arize’s mission is to make the world’s AI work and work for the people. Our founders came together through a common frustration: investments in AI are growing rapidly across businesses and organizations of all types, yet it is incredibly difficult to understand why a machine learning model behaves the way it does after it is deployed into the real world. 

If a machine learning team doesn’t have the tools to answer basic questions about a model’s performance metrics, how could they even attempt to answer more complex questions about the impact of these systems on the communities they are meant to serve?

From that passion emerged Arize, a machine learning observability platform to help unpack the proverbial AI black box. Our solutions provide ML teams the tools they need to understand whether their models are performing as expected in production and quickly get to the cause behind issues that emerge.

Arize was recently recognized by Forbes as one the Top 50 AI companies to watch in 2021. 

Learn more about Arize in an interview with our founders: Arize AI Helps Us Understand How AI Works