Principal Data Scientist

Do you want to be at the forefront of a team at Salesforce that is making history? Do you want to build technology and new science that millions of people will use? Are you excited about working on large scale Generative AI, Natural Language Processing (NLP), and Deep Learning?

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. Agentforce enables companies to scale their workforces on demand with a few clicks.

The Einstein GPT Data Science Team is looking for strong and recognized experts in Retrieval Augmented Generation (RAG), Knowledge Graphs and generative AI, to help design and develop intelligent, personalized and trusted CRM Generative AI Applications for Agentforce. In this position, you will be the principal scientific resource for full-cycle development (incubation, design, implementation, testing to documentation, and delivery) of our advanced RAG portfolio.

Our applied scientists are working on exciting and interesting problems in areas like advanced RAG technologies, Enterprise Knowledge Graphs, Search Relevance, LLM evaluations and metrics, feedback-based learning and parameter efficient fine-tuning. If you are interested in being part of a state-of-the-art foundational applied science team that has high visibility and customer impact, then reach out to join our team!

Basic Qualifications

1. PhD or equivalent Master's Degree plus 7+ years of experience in CS, CE, ML or related field
2. Experience with RAG, Knowledge Graphs, NLP methods and generative AI
3. Strong experience building and applying machine learning models for business applications
4. Strong experience programming in Python, and using machine learning frameworks such as TensorFlow or PyTorch
5. Proven ability to implement, operate, and deliver results via innovation at large scale

Preferred Qualifications

1. A PhD in CS, Machine Learning, Statistics or relevant field
2. 7+ years of industry/applied research experience in machine learning, NLP, deep learning and/or information retrieval
3. Proven expertise with RAG, knowledge graphs and search relevance
4. Strong background in ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian methods
5. Experience with conversational AI
6. Fantastic problem solver; ability to solve problems that the world has not solved before
7. Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams
8. Excellent written and spoken communication skills