Research Scientist - Salesforce AI Research

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Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

This role is only open to to prior Salesforce interns. All others who do not meet this criteria will not be considered.

Salesforce AI Research is looking for outstanding research scientists.

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

At Salesforce, we have launched Einstein GPT, the world’s first Generative AI for CRM, which delivers AI-created content across every sales, service, marketing, commerce, and IT interaction at hyper-scale. With Einstein GPT, Salesforce can transform every customer experience with generative AI.
Want to learn more? Check this out: Introducing Einstein GPT: The World's First Generative AI for CRM | Salesforce

Research scientists at Salesforce discover new research problems, develop novel models, design careful experiments, and advance the state of the art in AI. The research team is committed to collaboration with the wider research community. At Salesforce AI Research, we innovate by publishing at top academic conferences and filing patents. We embed our research work across Salesforce products for the worlds #1 AI CRM. We gain perspectives from product to research that help guide future directions. We believe that making substantive progress on hard applications can drive and sharpen the research questions we study, and in turn, scientific breakthroughs can spawn entirely new applications. Research scientists have the opportunity to switch between pure and applied research.

Check out our website to learn more about the groundbreaking work of the Salesforce AI Research team https://www.salesforceairesearch.com

Candidates have a strong background in one or more fields: Natural Language Processing, Large Language Modeling, Computer Vision, Reinforcement Learning, or Machine Learning in general.


Responsibilities:

• Own and pursue ambitious, long-term research goals.
• Develop solutions for real-world, large-scale problems.
• As needed lead teams to deliver on more complex pure and applied research projects.

Minimum qualifications:

• Ph.D./Master's degree in computer science, artificial intelligence, machine learning, or a related technical field.

• Strong publication record in top AI venues like NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ECCV, and ICCV.

• Experience with one or more general-purpose programming languages, including but not limited to C/C++ or Python.

• Experience with one or more deep learning libraries and platforms (e.g., TensorFlow, Jax, or PyTorch).

• Proven ability to implement, operate, and deliver results via innovation at a large scale.

• Large Language Models (LLMs), LLM evaluation and benchmarking, multilingual LLMs, LLMs as foundation of agents

Preferred qualifications:

• Full-time industry experience in deep learning research/product.
• Strong experience building and applying machine learning models for business applications.
• Experience training large language models.
• Experience mentoring and advising other researchers.
• Strong programming skills, competitive in ACM-ICPC or other competitions or open source experience is preferred.
• Experience in implementing high-performance and large-scale deep learning systems.
• Thoughtful about AI impacts and ethi