Research Intern
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Job Description
About the Company:
Salesforce Research is seeking outstanding research interns to contribute to their ongoing projects. The team focuses on advancements in various AI fields, with a particular emphasis on practical applications within Salesforce’s ecosystem.
Job Description:
Salesforce Research is looking for research interns with a strong background in one or more of the following areas:
• Conversational AI: Developing and improving conversational agents.
• Multimodal Data Intelligence: Working with data encompassing multiple modalities (e.g., text, images, audio).
• Multimodal Content Generation: Generating content across various modalities.
• Fundamentals of Machine Learning and AI: A solid theoretical understanding of machine learning and artificial intelligence principles.
• Responsible & Trusted AI: Researching and implementing ethical considerations in AI development and deployment.
• Natural Language Processing (NLP): Processing and understanding human language.
Areas of Application: Interns will contribute to research projects impacting these areas:
• Software Intelligence: Applying AI to improve software development and maintenance.
• AI for Operations: Utilizing AI to optimize operational efficiency.
• AI for Availability & Security: Enhancing system availability and security through AI.
• Environment & Sustainability: Developing AI solutions for environmental challenges.
Preferred Qualifications:
• Publications in top-tier conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR).
Responsibilities:
• Collaborate with a team of research scientists and engineers.
• Work on a research project with the potential for publication in a top-tier conference.
• Explore research areas outside of your immediate expertise.
• Conduct pure research that aligns with your PhD focus and contributes to the broader AI community.
• Attend conferences with Salesforce researchers to present accepted papers.
Requirements:
• Currently pursuing a PhD in a relevant research area.
• Excellent understanding of deep learning techniques, including CNNs, RNNs, LSTMs, GRUs, GANs, attention models, and optimization methods.
• Experience with at least one deep learning library/platform (e.g., PyTorch, TensorFlow, Caffe, Chainer).
• Strong background in at least one of the following: machine learning, natural language processing, computer vision, or reinforcement learning.
• Strong algorithmic problem-solving skills.
• Programming experience in Python, Java, C/C++, Lua, or a similar language.
• Minimum internship duration: 12 weeks.
