Search Relevance ML Engineer/Data Scientist – Lead

Job Type: Full Time
Job Location: USA
Company Name: Salesforce

Responsibilities

  • Design, develop, and scale AI-powered search features for a high-performance search service handling millions of daily queries across structured, unstructured, and social data.
  • Develop and operationalize usage metrics to identify patterns and optimize search relevance.
  • Analyze product, device, and use case interactions across Salesforce to enhance search experiences.
  • Deploy machine learning models at scale and evaluate their impact through A/B testing and result interpretation.
  • Innovate relevance algorithms and techniques, leveraging the latest advancements in research.

Required Skills

  • 8+ years of hands-on experience in Machine Learning, Information Retrieval, Recommendation Systems, Personalization (p13n), Natural Language Processing, Learning to Rank, and Retrieval-Augmented Generation (RAG).
  • Proficiency in AI frameworks like TensorFlow and PyTorch.
  • Strong knowledge of measuring and quantifying search relevance performance.
  • Experience deploying and managing AI solutions on cloud platforms like AWS SageMaker and Amazon Bedrock.
  • Expertise in building enterprise-scale applications with Large Language Models (LLMs) and fine-tuning them.
  • Strong programming skills in Python and Java.
  • Deep understanding of object-oriented design, advanced algorithms, and data structures.
  • Ability to analyze large datasets, integrate new data sources, and optimize machine learning models.
  • Excellent written and verbal communication skills.

Desired Skills

  • Master’s or Ph.D. in a relevant field or extensive experience in machine learning, data science, classification, regression, and Bayesian analysis.
  • Experience working with search systems like Lucene or Solr.
  • Proficiency in big data tools such as Hadoop, Spark, Pig, or Hive.
  • Strong grasp of usability and visual design principles.
  • Expertise in A/B testing, metric definition, and analysis.
  • Experience in developing Software-as-a-Service (SaaS) applications.
  • Familiarity with Agile development and Test-Driven Development (TDD) methodologies.

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