| Company | Salesforce |
| Job title | Search Relevance ML Engineer/Data Scientist – Lead |
| Job location | California – San Francisco/Washington – Seattle/Washington – Bellevue |
| Type | Full Time |
Responsibilities:
Design, develop, bring to production at a large scale, and support “intelligence” features on an outstanding search service that serves millions of requests daily on a diverse corpus of data, including structured, unstructured, and social feeds.
Design and operationalize usage metrics and patterns to find opportunities to improve the relevancy of search.
Analyze and understand the different products, devices, and use cases that are driven by search across Salesforce and develop strategies for improving relevancy.
Deploy models at scale and assess impact from A/B testing (including interpretation of results).
Develop new relevance features and techniques, and build upon the latest results from the research community.
Requirements & Skills:
- At least 8 years of hands-on experience in engineering positions, passionate about Machine Learning, Information Retrieval, Recommendation systems, Personalization (p13n), Natural Language Processing, Learning to Rank, RAG
- Experience with AI frameworks like Tensorflow, Pytorch
- Understanding how to measure and quantify the quality of search relevance systems
- Experience deploying and managing AI solutions on cloud platforms such as AWS SageMaker and Amazon Bedrock
- Experience building applications with Large Language Models and the ability to fine-tune them for enterprise scale.
- Strong programming skills in Python and Java.
- Strong understanding of object-oriented design, advanced algorithms, data structures, etc.
- Iteratively analyzing data, integrating new data sources, experimenting, and optimizing.
- Excellent oral and written communication skills
- Master’s or PhD in a relevant field and/or experience in any of the following is highly regarded: Machine learning, data science, and modeling techniques, including classification, regression, and Bayesian analysis.
- Experience with Lucene/Solr or similar search systems is preferable
- Experience working with large datasets, preferably using tools like Hadoop, Spark, Pig, or Hive.
- Good understanding of usability and visual design principles
- Understanding of A/B testing, expertise in metric definition and analysis
- Experience building Software as a Service (SaaS) applications
- Experience with Agile software development and Test Driven Development methodologies
