Research Scientist - Salesforce AI Research

Salesforce•Palo Alto, CA

21d

About The Position

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Salesforce AI Research is looking for outstanding AI Research Scientists / Research Engineers. Do you want to be at the forefront of a team at Salesforce that is making history? Do you want to develop new technology and science that millions of CRM customers will use? Are you excited about working on large-scale Generative AI, Agentic Systems, Speech Intelligence, and Multimodal Deep Learning? Our team discovers new research problems, develops novel models, and bridges the gap between groundbreaking theory and customer-facing reality. We are dedicated to a high-impact research model that provides the best of both worlds: the ability to advance the state-of-the-art in AI and the opportunity to see that work operate at massive, real-world scale within the world’s #1 AI CRM. We believe that making substantive progress on hard, enterprise-level applications drives and sharpens the research questions we study. Check out our website to learn more about the groundbreaking work of the Salesforce AI Research team: https://www.salesforceairesearch.com Candidates have a strong background in one or more of the following areas: Agentic AI & Reasoning: LLM-powered agents, reinforcement learning, and autonomous workflows. Multimodal & Computer Vision: Vision-language models (VLM), video understanding, and visual grounding for GUI agents. Speech Intelligence: Voice intelligence, TTS/ASR, human-like turn-taking, and low-latency audio processing. Efficient Systems: Scalable deep learning infrastructure, high-performance audio/video pipelines, and low-latency deployment. Core Modeling: Machine learning methodology, pre-training/post-training (RLHF, DPO), and model distillation.

Requirements

Ph.D., Master’s, or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
A strong publication record in top AI venues (e.g., NeurIPS, ICLR, ICML, CVPR, ICCV, ACL, EMNLP) OR a proven track record of shipping AI products to real users.
Demonstrated expertise in one or more core focus areas: LLMs, Agentic Systems, Computer Vision/Multimodal, Speech Intelligence, or Research Engineering.
Experience with Python and deep learning libraries/platforms (e.g., PyTorch, Jax, or DeepSpeed).
Proven ability to implement, operate, and deliver results via innovation at a large scale.

Nice To Haves

Full-time industry experience in deep learning research and/or product development.
Experience training and evaluating large-scale multimodal models or speech models, including techniques for alignment, safety, and latency optimization.
Experience with production cloud deployments (AWS/GCP), container orchestration (Kubernetes), or high-performance systems (MLOps).
Strong programming skills, with a competitive background (e.g., ACM-ICPC or significant open-source contributions) or experience in UI/graphic design.
Thoughtful about AI impacts, trust, and ethics.
Outstanding communication, collaboration, and problem-solving skills.

Responsibilities

Own and pursue ambitious research and engineering goals aligned with strategic initiatives.
Develop novel models and technical solutions for real-world, large-scale problems within the enterprise ecosystem.
Design, build, and maintain production-ready services, including scalable APIs and agentic evaluators.
Collaborate across a strike-team of researchers and engineers to deliver complex projects that directly impact our core AI products and customer experiences.