AI Scientist

4 days ago


Stanford, United States Salesforce Full time

AI Scientist Job Description Salesforce is the global leader in Cloud-based (SaaS) solutions that enable the worlds premier brands to maintain a robust online presence with high ROI. We do that by providing a highly scalable, integrated cloud platform that allows our clients to rapidly launch and manage multiple e-commerce stores, initiate unique marketing campaigns, and drive customer traffic across a global footprint. We are looking for a top-notch AI scientist to join the Agentforce org. Our team of applied AI scientists is tasked with building, optimizing, and innovating the Agentforce planner system. This means you will work on how to best utilize frontier foundational models for real-world use cases, including exploring innovative approaches to agent systems and taking on the complex challenge of building testing frameworks and test cases. You will research, design, and prototype, in close collaboration with engineering and product teams and learn from customer deployments. We are looking for someone who gets a kick out of staying on top of the latest AI literature, tools, and techniques and figuring out the best way to apply these for practical solutions. We encourage contribution to tools and knowledge sharing within the team, the company, and the industry. Responsibilities Work with product management and leadership to translate business problems into applied science problems Research, prototype, and build demonstrations of AI ideas for quick validation and feedback Design and build AI systems to hit accuracy and performance metric targets Productize AI innovations in collaboration with engineering teams Educate engineering and product teams about AI science during collaboration Mentor and collaborate with other members of the team Share technical innovations with the team and across the company Create innovations and contribute to conferences and/or open-source tools Qualifications Must-Have Fluent in prototyping AI solutions, testing machine learning models, and wrangling small/medium-sized datasets BS/MS in a quantitative discipline with 7 years of relevant experience Expertise in classical machine learning, deep learning, and large-language-models (LLMs) Avid experimenter in all things LLMs and agent systems towards innovating how current AI solutions are built Proficient in using Python scientific stack (e.g. Numpy, Pandas, PyTorch, SciPy, Jupyter) Proficient in shell scripting, Unix/Linux command-line tools, and working with cloud infrastructure (AWS) Great communication skills: ability to discuss with scientists, engineers, designers, and product managers Nice to have Experience in building agent systems and shipping to production Ph.D. with 1 years of relevant experience 7 years of deep experience in reinforcement learning, deep learning, causal inference, and information retrieval Open-source machine learning code from one's paper, contributions to any projects, implementations of papers Publications in any of {cvpr, iccv, eccv, neurips, iclr, icml, acl, emnlp, recsys, kdd} J-18808-Ljbffr


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