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# Machine Learning Engineer

- **Company:** Yobi Corporation
- **Location:** New York, NY, United States (Remote available)
- **Salary:** $180,000.0 - $275,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Big Data, Continuous Integration, Github, Machine Learning, Open Source Technology, Data Processing, Apache Spark, Build Tools, Data Pipelines
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/machine-learning-engineer-core-signals-yobi-6242616

## About the Role

* You understand enough about machine learning to be able to apply it to novel problems and suggest improvements to our current setup, or even radical new approaches. Previous publication experience is not required.
 * You've worked on and can speak to at least some of: representation learning, embeddings drift, CTR modeling, sequence modeling, etc., preferably on "big data" in an industrial setting.
 * Skill and attitude wise, you can quickly contribute to the non-research components of our pipeline. This includes things such as data orchestration, build systems, and experiment tracking. Although we use a combination of open source products like Airflow, Bazel, Github CI/CD, and Spark, prior experience with these specific solutions is not needed. However, a good part of your day to day will involve interacting with these systems, so you should be comfortable with getting your hands dirty.
 * Good product sense - you have opinions on what we should and shouldn't be doing both in chasing product-market fit and on the implementation side.

## Description

As an MLE on the Core Signals team, you will primarily be focused on (1) the representation learning surrounding our fundamental user-behavioral modeling problems and (2) using those core models to power new and existing products.

This role involves a lot of collaboration with the Product org and Applications team to realize these R&D gains - but is ultimately a "full stack" ML role. Day to day responsibilities include data processing, model training, deployment, and evaluation.

A good amount of "wearing your Product hat" is expected, as well as the ability to flex into some other functions as needed - we are a quickly growing startup after all.


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