About the job
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. 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.
Responsibilities
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).
Qualifications
Minimum
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, TensorFlow).
Strong algorithmic problem-solving skills.
Programming proficiency in Python, Java, C/C++, Lua, or a similar language.
Preferred
Candidates that have published in top-tier conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, CHI) are highly preferred.