Lead Applied Scientist

Company:  Salesforce, Inc.
Location: San Francisco
Closing Date: 22/10/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

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?

At Salesforce, we have launched EinsteinGPT, the world’s first Generative AI for CRM, which delivers AI-created content across every sales, service, marketing, commerce, and IT interaction, at hyperscale. With Einstein GPT, Salesforce can transform every customer experience with generative AI.

The Einstein GPT Data Science Team is looking for strong and recognized experts in NLP and generative AI, to help design and develop intelligent, personalized and trusted CRM Generative AI Applications. Our data scientists are working on exciting and interesting problems in areas like Advanced RAG and retrievers, Knowledge Graphs, LLM evaluations and metrics, feedback-based learning, parameter efficient fine-tuning, reinforcement learning, LLM alignment, bias mitigation, and multilingual support. If you are interested in being part of state-of-the-art foundational applied science that has high visibility and customer impact, then reach out to join our team!


Basic Qualifications

  • PhD or equivalent Master's Degree plus 5+ years of experience in CS, CE, ML or related field
  • Strong experience with NLP, deep learning, and generative models
  • Strong experience building and applying machine learning models for business applications
  • Strong experience programming in Python, and using machine learning frameworks such as TensorFlow or PyTorch
  • Proven ability to implement, operate, and deliver results via innovation at large scale

Preferred Qualifications

  • A PhD in CS, Machine Learning, Statistics or relevant field
  • 5+ years of industry/applied research experience in machine learning, NLP, deep learning and/or information retrieval
  • Expertise with applying LLMs, prompt design, and fine-tuning methods
  • Strong background in ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian methods
  • Experience with conversational AI
  • Top-tier papers published in related areas.
  • Fantastic problem solver; ability to solve problems that the world has not solved before
  • Excellent written and spoken communication skills
  • Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams
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