Yahoo

Senior Machine Learning Engineer

Yahoo

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $128,250 - $266,875 per year

Job Level

Senior

Tech Stack

AWSAzureCloudGoogle Cloud PlatformHadoopJavaPythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

  • Design, develop, and maintain advanced machine learning models and systems focused on ranking, recommendation, and content understanding
  • Collaborate with product managers, data scientists, and software engineers to integrate machine learning solutions into product infrastructure
  • Monitor and evaluate performance of machine learning systems in production using metrics to guide improvements
  • Drive development and implementation of MLOps practices to ensure scalability and efficiency of ML workflows
  • Translate complex business requirements into robust technical solutions
  • Adhere to Yahoo policies; exercise sound judgment; work effectively, safely and inclusively; exhibit trustworthiness and safeguard business operations and brand integrity

Requirements

  • Bachelor’s or Master’s in Data Science, Mathematics, Statistics, Economics, Computer Science, or a related field
  • 8+ years of software engineering experience
  • Strong expertise in machine learning, NLP, and recommender systems for content classification and personalization
  • Proficiency in Python, Java, or Scala
  • Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
  • Experience working with large-scale datasets and distributed computing (Spark, Hadoop)
  • Experience with cloud platforms (AWS, GCP, or Azure)
  • Experience with continuous integration/continuous deployment (CI/CD) practices
  • Strong understanding of metadata extraction, named entity recognition (NER), and semantic search technologies
  • Proven ability to scale and optimize ML models for production environments
  • Solid foundation in machine learning operations (MLOps) and automating ML workflows
  • Strong communication skills and ability to translate complex business requirements into technical solutions
  • Customer-focused mindset and bias for action
  • Publications or presentations on recommendation systems (preferred)
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