Salesforce Research (previously MetaMind) is looking for outstanding entry level research scientists.
Research 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. Research scientists have the freedom to set their own research agenda and move between pure and applied research.
Ideal candidates have a strong background in one or more of the following fields: deep learning, machine learning, natural language processing, computer vision, or reinforcement learning. Additionally, applicants should have in-depth experience with one or more of text categorization, text summarization, information extraction, question answering, dialogue learning, machine translation, language and vision, image classification, image segmentation, or object detection.
Candidates should have a strong publication record in top-tier conferences or journals (e.g. NIPS, ICML, ICLR, ACL, CVPR, KDD, PAMI, JMLR, TACL, IJCV).
In addition to their own research agenda, senior research scientists will have the opportunity to take on additional responsibilities leading project teams, mentoring interns, and advising junior research scientists.
Participate in cutting edge research in machine intelligence and machine learning applications.
Develop solutions for real world, large scale problems.
Find and build ambitious, long-term research goals.
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 NIPS, ICML, ICLR, ACL, and CVPR.
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.