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Machine Learning Architect - Search & Knowledge Graphs
Salesforce is seeking a visionary Machine Learning Architect to lead advancements in intelligent Search and Knowledge Graph solutions within our Einstein Foundation team. Do you want to build next-gen Generative AI platforms for Empowering Enterprise Wide Knowledge Discovery, Accelerating AI with Knowledge Driven Context, Human Like Understanding of Relationships and Context using Knowledge graphs ?
Salesforce, the world's #1 AI CRM, has recently unveiled Agentforce, a groundbreaking suite of autonomous AI agents that augment employees and handle tasks in service, sales, marketing, and commerce, driving unprecedented efficiency and customer satisfaction.
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), 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. Our team values innovation, multi-functional collaboration, and a commitment to scaling AI driven customer success solutions.
The Role
In this role, you will architect and drive the development of intelligent Search and Knowledge Graph solutions at scale, integrating the latest advancements in machine learning, LLMs, and vector databases. You will be responsible for leading the end-to-end AI lifecycle, from conceptualization through production, focusing on scalable search and retrieval architectures optimized for enterprise use cases. As a motivated leader with a point of view, you will define standard methodologies and collaborate closely with Product Managers, Data Scientists, and Research teams to shape and deliver groundbreaking AI experiences.
What You'll Do:
- Lead the Architecture of Sophisticated Search & Knowledge Graph Solutions
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. - Develop Intelligent Retrieval Pipelines
Innovate hybrid retrieval pipelines combining semantic, vector, and symbolic search to improve contextual relevance, speed, and accuracy in knowledge driven AI applications. - Optimize and Automate Search Systems
Enhance system efficiency through automation in demand forecasting, configuration, and proactive monitoring, driving real time search optimization. - 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 and retrieval solutions. - 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.
Required Skills:
- 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 realtime, 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.
Preferred Search & Knowledge Graph-Specific Skills:
- Experience with Multi-Stage Retrieval Pipelines
Hands-on experience in designing and optimizing multi-stage retrieval workflows that balance precision, recall, and relevance at scale. - In-Depth Knowledge of Re-Ranking & Retrieval Optimization
Expertise in retrieval-specific optimizations, including re-ranking, hybrid search, and knowledge augmented retrieval, to improve relevance in enterprise-scale systems. - Graph Embedding & Contextual Retrieval Expertise
Confirmed skills in graph based search, context expansion techniques, and Knowledge Graph integration to enhance retrieval depth and accuracy. - Knowledge Graph Curation & Ontology Management
Experience in Knowledge Graph curation, schema design, and ontology management, ensuring efficient and adaptable knowledge driven search solutions. - Familiarity with Feedback Loops and Fine-Tuning
Knowledge of incorporating user feedback and relevance signals to fine-tune contextual embeddings and improve Search and Knowledge Graph system performance.
Additional Preferred Skills:
- Broad ML Experience with Diverse Approaches
Strong foundation in diverse ML techniques, from neural networks to probabilistic models, adaptable for Search and Knowledge Graph-centric AI use cases. - Exceptional Communication and Collaboration Skills
Outstanding written and verbal communication abilities, with confirmed expertise in collaborating across engineering, research, and product teams.
If you're an industry leader passionate about Search, Knowledge Graphs, and innovative AI, and eager to make an impact at the world's #1 CRM company, we'd love to meet you!
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Posting Statement
At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com.
Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.
Salesforce welcomes all.
Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
For Washington-based roles, the base salary hiring range for this position is $224,100 to $341,900.
For California-based roles, the base salary hiring range for this position is $244,500 to $372,900.
Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.