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.
Our Backend Engineering team builds all of the highly scalable distributed services that power Arize’s ML observability platform. The expectation and scope of every individual on this team is high, whether it’s finding the most efficient way to compute model evaluation metrics across billions of data points, or designing the next generation of our OLAP database architecture, or researching and implementing the latest dimensionality reduction techniques – you will never lack a technical challenge.
Being the team that is part of driving core innovation at Arize, you will have a material impact on the company’s ultimate success in this highly technical space. You’ll not only be able to contribute to projects, but also inform the team culture, structure, and practices as we scale.
What You’ll Do
What We’re Looking For
Bonus Points, But Not Required
The estimated annual salary for this role is between $100,000 - $185,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.
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.
Learn more about Arize in an interview with our founders: https://www.forbes.com/sites/frederickdaso/2020/09/01/arize-ai-helps-us-understand-how-ai-works/#322488d7753c
Diversity & Inclusion @ Arize
Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture