Artificial Intelligence Architect

3 days ago

San Francisco, California, United States Salesforce Inc Full time

Company Overview: Salesforce Inc. is a global leader in customer relationship management, empowering businesses to connect with their customers in a more personalized way.

About the Role:

We are seeking an exceptional Artificial Intelligence Architect to lead advancements in scalable search solutions within our Einstein Foundation team.

This role is pivotal in redefining how we enable innovative, knowledge-driven experiences across Salesforce's next-gen AI products.

You will drive the evolution of Salesforce's AI systems with innovative retrieval, representation, and context expansion technologies that serve millions of users globally.

The Team:

Our Einstein Foundation team is an interdisciplinary mix of machine learning engineers, data scientists, and software engineers working collaboratively to build adaptive, context-aware systems that elevate customer interactions and insights.

Job Responsibilities:

  1. Design and Implement Advanced Search Systems: Architect and implement end-to-end, large-scale search solutions optimized for high-performance, multi-tenant environments.
  2. Innovate Hybrid Retrieval Pipelines: Develop hybrid retrieval pipelines combining semantic, vector, and symbolic search to improve contextual relevance, speed, and accuracy in knowledge-driven AI applications.
  3. Optimize and Automate Search Systems: Enhance system efficiency through automation in demand forecasting, configuration, and proactive monitoring, driving real-time search optimization.
  4. Collaborate Across Teams for AI-Driven Product Innovation: Work closely with multi-functional teams, including Product Managers, Knowledge Engineers, and ML Researchers, to assemble requirements and translate them into scalable, innovative search solutions.
  5. Pioneer Search and Knowledge Graph Innovations: Guide discussions on emerging technologies and advancements in vector search, graph embeddings, and knowledge-augmented retrieval, valuing continuous innovation.

Requirements:

  • 15+ years in Machine Learning & Search Systems: Extensive experience with large-scale search, Machine Learning, and knowledge-driven systems, specifically focused on integrating Knowledge Graphs, search optimization, and sophisticated retrieval techniques.
  • Expertise in Semantic and Vector-Based Search: Deep knowledge of vector databases (e.g., FAISS, Pinecone, Milvus), approximate nearest neighbor (ANN) search algorithms, and embedding techniques to power high-relevance search systems.
  • Strong Background in NLP & LLMs: Experience with natural language processing (NLP), prompt engineering, and applying LLMs to enhance knowledge-based search and retrieval in enterprise contexts.
  • Sophisticated Knowledge Graph Skills: Proficiency in graph databases (e.g., Neo4j, Amazon Neptune), graph embedding, and linking techniques to enable rich contextual search and high-dimensional graph-based retrieval.
  • Proficiency in Distributed Systems & ML Frameworks: Authority understanding of distributed systems, data streaming (e.g., Kafka, Spark), and Machine Learning frameworks (TensorFlow, PyTorch) to support real-time, resilient AI applications.
  • Programming Mastery in Python & Graph-Based Frameworks: Strong programming skills in Python, with expertise in machine learning and graph-based frameworks to facilitate scalable, high-performance AI solutions.

Compensation Package: The salary range for this position is $224,100 to $341,900 based on location in Washington or $244,500 to $372,900 based on location in California.

Work Location: This role can be performed remotely or from our San Francisco or Los Angeles offices.

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