Summer Intern AI Research

Salesforce AI Research

advances AI techniques that pave the path for new AI research directions, innovative products, and applications with a positive impact on society. Our team of researchers, engineers, product managers, and designers drives AI innovation across pure research, applied research, and new product incubation-all built on our powerful AI platform. We bring companies and customers together using explainable, transparent, and accountable AI
.

As part of our team, you'll gain unique skills, work with talented people, and influence the industry standard for the fair and ethical use of artificial intelligence to help us shape the future of AI.

Check out our website to learn more about the groundbreaking work of the Salesforce AI Research Team .

Salesforce Research is looking for outstanding research interns
. Ideal candidates have a strong background in one or more of the following core areas:

• Natural Language Processing (NLP)
• Computer Vision (CV)
• Reinforcement Learning (RL)
• General Machine Learning (ML)

Our research focus includes, but is not limited to, the following cutting-edge areas:

• AI Agents
• Large Language/Action Modeling
• Responsible & Trusted AI
• Human-AI Interaction
• AI for Software Developers
• AI for Operations / Time Series
• AI for Knowledge Management
• Mobile AI
• Multimodal AI
• Automatic Evaluation

Candidates that have published in top-tier conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, CHI) are highly preferred.

• Collaborate with a team of research scientists and engineers on a project designed to lead to a submission at a top-tier conference.
• Develop novel algorithms and techniques that can be applied to real-world customer challenges within the Salesforce ecosystem.
• Contribute to the AI community by focusing on pure research that aligns with your PhD focus area.
• Learn about exciting research and applications outside your expertise.
• Attend conferences with our researchers to showcase accepted papers (when applicable).

• PhD or MS candidate in a relevant research area.
• Strong background in machine learning, natural language processing, computer vision, or reinforcement learning.
• Excellent understanding of deep learning techniques, including CNN, RNN, LSTM, GAN, attention models, and optimization methods.
• Experience with one or more deep learning libraries and platforms (e.g.,
  PyTorch, Tensor Flow ).
• Strong algorithmic problem-solving skills.
• Programming proficiency in Python , Java, C/C++, Lua, or a similar language.

This internship is a minimum of 12 weeks
.