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# Senior Machine Learning Engineer - Content and Contributor Intelligence (Remote - United States)

- **Company:** Yelp, Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $112,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Neural Networks, Computer Vision, C++ (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Pytorch, Large Language Models, Prompt Engineering, Spark Mllib, Scikit Learn, Xgboost, Software Coding, Data Pipelines
- **Published:** August 25, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pecj26e8g0

## About the Role

* Experience developing and productionizing machine learning models, particularly in neural networks, computer vision and LLMs including their supported data pipelines.
 * Experience with machine learning using packages such as PyTorch, TensorFlow, Spark MLlib, XGBoost, and Sklearn.
 * Strong coding skills in Python or equivalent (Java, C++).
 * Solid understanding of engineering and infrastructure best practices.
 * The curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal.
 * We highly value experience of working with LLMs, utilizing LLM APIs (OpenAI, Bedrock, etc), prompt engineering and evaluation.
 * A Bachelor's Degree or an equivalent work experience is required

## Description

* Conduct end-to-end analyses, wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
 * Mentor and guide junior engineers, fostering a culture of learning and technical excellence.
 * Work with large and complex textual and visual datasets.
 * Support the development and deployment of projects involving machine learned models for offline, batch-based data products as well as models deployed to online, real-time services.
 * Work in the contributor and visual intelligence team on text and visual understanding, along with fine tuning transformer models to derive embeddings for multiple input types
 * Productionize and automate model pipelines within Python services.
 * Drive and advocate adoption of best practices in ML development and operations, and mentor newer engineers in those practices.


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