AI Scientist
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/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 build
Proficient in using Python scientific stack (e.g. Numpy, Pandas, PyTorch, SciPy, Jupyter)
Proficient in shell scripting, Unix/Linux command-line tools, 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}
Apply Now
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/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 build
Proficient in using Python scientific stack (e.g. Numpy, Pandas, PyTorch, SciPy, Jupyter)
Proficient in shell scripting, Unix/Linux command-line tools, 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}
Apply Now