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Job Category Products and Technology
Salesforce Research is looking for outstanding applied scientists.
Applied scientists discover new research problems, develop novel models, design careful experiments and generally advance the state of the art in AI. At Salesforce, the research team is committed to collaboration with the wider research community; while research scientists have the opportunity to work directly on advancing technologies that customers use as part of the Einstein Platform, they may also focus exclusively on publications. 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. With this in mind, the team maintains a portfolio of projects, some with an immediate path to production, others that may not find an application for several years. Applied scientists have the opportunity to switch between pure and applied research.
Candidates have a strong background in one or more of the following fields: natural language processing, computer vision, reinforcement learning, economics, deep learning or machine learning.
Ideally, applicants should have in-depth experience with one or more of text categorization, text summarization, information extraction, question answering, dialogue learning, machine translation, or language and vision.
Ideally, applicants should have in-depth experience with one or more of image and video understanding, OCR/Document AI, self-supervised learning, multi-modality learning, AI robustness/ethics, generative learning.
- Own and pursue ambitious, long-term research goals.
- Develop solutions for real world, large scale problems.
- As needed or desired, lead teams to deliver on more complex pure and applied research projects.
- PhD degree in computer science, artificial intelligence, machine learning, or related technical field.
- Strong publication record in machine learning, NLP, computer vision, reinforcement learning, or optimization, especially at venues like NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ECCV, 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, Caffe, Chainer or PyTorch).
- Full time industry experience in deep learning research/product.
- Experience mentoring and advising other researchers.
- Strong programming skills, competitive in ACM-ICPC or other competitions.
- Experience in implementing high-performance and large scale deep learning systems.
- Thoughtful about AI impacts and ethics.
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