Arize AI

Backend Engineer

Remote
USD 100k - 185k
Go API Python Kubernetes Kafka Machine Learning Java AWS GCP Azure
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Description

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 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

  • Write maintainable, scalable performant Go.
  • Build high volume and highly available analytics systems.
  • Design and build APIs specific to our customers’ ML workflows.
  • Prototype, optimize, and maintain scalable backend services that power Arize core platform.
  • Extend, and contribute back to, open source OLAP databases and distributed message queue frameworks.
  • Research and implement cutting edge visualization & dimensionality reduction algorithms in a distributed environment.
  • Collaborate with our product, design, and backend engineering teams in order to enhance and expand our product offering.

What We’re Looking For

  • 3+ years of experience working with high performant backend systems
  • Strong experience writing Go, Python, Java, or similar server programming languages
  • Strong experience writing concurrent and distributed programs.
  • Previous work building and operating highly complex SaaS platforms / systems.
  • Knowledge working with public clouds & container orchestration - AWS, GCP, Azure, Kubernetes, etc.

Bonus Points, But Not Required

  • Experience with distributed stream processing - Kafka, Gazete, or similar
  • Experience with OLAP systems
  • Familiarity with system observability tooling like Prometheus
  • Working knowledge of Machine Learning and/or Data Science

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

  • Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI
  • Culturally conscious events such as LGBTQ trivia during pride month
  • We have an active Lady Arizers subgroup
Arize AI
Arize AI
Artificial Intelligence (AI) Information Technology Machine Learning Software

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