Job Description

Location: Singapore - Singapore Salesforce Research is pioneering in the field of deep learning, natural language processing and artificial intelligence. At Salesforce, the research team is committed Location: Singapore - Singapore Salesforce Research is pioneering in the field of deep learning, natural language processing and artificial intelligence. At Salesforce, the research team is committed to collaborating 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 AI Platform, they may also focus exclusively on high-impact 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 immediate application for several years. As a Research Scientist at Salesforce Research Asia, your role will be at the intersection of software engineering and research, and may range from implementing novel research models to rapid-prototyping demos that show off applications of machine learning on real-world data. You will work closely with research scientists to develop models, prototypes, and experiments that push the state of the art in AI research, paving the way for innovative products and services. You will have the opportunity to take on real-world problems from Salesforce's enterprise customers with the latest AI methods. You will primarily work on one of the following two selected areas: (1) AI for IT Operations (AIOps) and related research areas, such as Time-series Analysis, Root Cause Analysis (RCA), Incident Management, Anomaly Detection, Causal ML for AIOps, Planning and Optimization, Auto-remediation, ML platforms for AIOps, etc (2) AI for Software and related research areas, such as AI for software applications, large-scale code pre-training, AI for code generation, AI for code understanding, bug detection/localization, automatic program repair, AI coding assistant, etc. You should have strong programming skills and have research experience or background in one or more of the following domains: machine learning, deep learning, natural language processing (NLP), data mining, software engineering, etc. Responsibilities Participate in cutting-edge research in machine learning, AI for IT Operations (AIOps), or AI for Software Develop innovative and scalable solutions for large-scale, real-world problems in AIOps or software related domains Minimum Qualifications BA/BS/MS/PhD degree in CS, EE, or other related computer science or engineering degree with 5+ years industry experience in AI / ML / DL with application to domains such as Software Engineering, Cloud computing, Site Reliability Engineering, or relevant fields. Experience and Proficiency with one or more general purpose programming languages including but not limited to: Python, Java, C/C++. Experience with one or more machine learning and deep learning libraries (e.g., TensorFlow, PyTorch, etc). Experience with machine learning platform, software engineering, cloud computing and distributed systems, and you are able to build, test and deploy code to cloud infrastructure Practical experience in AIOps related projects (such as Root cause analysis, anomaly detection, incident management, failure detection, prediction and prevention, auto-remediation, resource scheduling and provisioning, etc.) or AI Software related projects (large-scale software code pretraining, defect detection, bug localization, automated program repair, code auto-completion, code generation, code search, etc). Bonus Points Practical applied research experience in building and iterating AI products with machine learning, deep learning, NLP, data science, or related technology. Exposure to industry applied research or academic research, have a track record of having published papers in top-tier conference/journal venues (e.g. ICML, NeurIPS, ICLR, ACL, CVPR, ICSE, USENIX, etc.). Managerial skills, and have led teams to deliver AI Research and AI Products Strong programming skills, competitive in ACM-ICPC or other competitions. Expert in large-scale deep learning system, train models with GPU/TPU parallelisation. Experience in GPU programming, data visualisation, or web/mobile development.