Senior Machine Learning Engineer - Gen AI and Product Applications - Anomalo

Please Note: This role is only open to candidates who currently reside in and have authorization to work in the US. 

Machine Learning Engineer – Gen AI & Product Applications

We’re looking for a Machine Learning Engineer to help build, deploy and support Anomalo’s suite of Generative AI products that process unstructured data and support enterprise customers. This role is part of a new 0-1 product team, where you'll shape product quality and integrate multiple LLMs into real-world applications.

What You’ll Do

What We’re Looking For

Nice to Have

Why Join Us?

This is a unique opportunity for an ML engineer who thrives in building and launching real-world AI products. If you're excited about applying LLMs to practical use cases, we’d love to hear from you!



Perks of working at Anomalo:

Many of our benefits and perks are designed for full-time employees, with some available only to team members based in the United States.

What we value:

About Anomalo

Anomalo is the automated AI solution that integrates with the modern data stack to monitor data quality. Using unsupervised learning, it detects complex issues like distribution changes that static rules miss. With built-in root cause analysis, Anomalo identifies anomalies, their causes, and their impact, helping data teams focus on building instead of debugging.

We’re rapidly growing and work with some of the biggest brands leveraging data today, like Block, Discover, Atlassian, and Included Health. Backed by $82M in seed through Series B extension funding from top-tier firms, including SignalFire, Norwest Venture Partners, Databricks Ventures, Foundation Capital, Two Sigma Ventures, and First Round Capital, Anomalo is enabling companies to make better data-driven decisions.

 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the  interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for confidential accommodation requests will be shared.
 
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