AI Search Architect
3 weeks ago
About the Opportunity
Salesforce is seeking a visionary leader to drive advancements in intelligent Search and Knowledge Graph solutions within our Einstein Foundation team. The successful candidate will be responsible for architecting and developing next-gen Generative AI platforms for Empowering Enterprise Wide Knowledge Discovery, Accelerating AI with Knowledge Driven Context, and Human Like Understanding of Relationships and Context using Knowledge graphs.
The ideal candidate will have extensive experience with large-scale search, Machine Learning, and knowledge driven systems, specifically focused on integrating Knowledge Graphs, search optimization, and sophisticated retrieval techniques. They will lead the end-to-end AI lifecycle, from conceptualization through production, focusing on scalable search and retrieval architectures optimized for enterprise use cases.
This role is pivotal in redefining how we enable innovative, knowledge driven experiences across Salesforce's next-gen AI products. As an authority in Search, Knowledge Graphs, and Large Language Models (LLMs), the successful candidate will drive the evolution of Salesforce's AI systems with innovative retrieval, representation, and context expansion technologies that serve millions of users globally.
Key Responsibilities
- Architect and implement end-to-end, large scale search and retrieval solutions that demonstrate Knowledge Graphs and are optimized for high-performance, multi-tenant environments.
- Innovate hybrid retrieval pipelines combining semantic, vector, and symbolic search to improve contextual relevance, speed, and accuracy in knowledge driven AI applications.
- Enhance system efficiency through automation in demand forecasting, configuration, and proactive monitoring, driving real time search optimization.
- Work closely with multi-functional teams, including Product Managers, Knowledge Engineers, and ML Researchers, to assemble requirements and translate them into scalable, innovative search and retrieval solutions.
Requirements
- 15+ years in Machine Learning & Search Systems
- Expertise in Semantic and Vector-Based Search
- Strong Background in NLP & LLMs
- Sophisticated Knowledge Graph Skills
- Proficiency in Distributed Systems & ML Frameworks
- Programming Mastery in Python & Graph Based Frameworks
Compensation Package
We offer a competitive compensation package, including a base salary of $244,500 - $372,900 per year, depending on location and level of experience. Additional benefits include comprehensive health insurance, retirement savings plan, paid time off, and opportunities for professional growth and development.
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