S
Not Specified Permanent

San Francisco, California · USA job

Research Scientist - Salesforce AI Research

Salesforce

San Francisco, California

Job description

Overview

In this role, you contribute to Salesforce AI Research, advancing AI at enterprise scale for CRM. You will develop novel models and systems that impact millions of users, while delivering production-ready services and collaborating with a cross-disciplinary team. The work blends cutting-edge research with real-world deployment, shaping products and customer experiences. This is a chance to influence the trajectory of AI in a world-leading CRM platform and be part of a mission-driven, innovation-focused culture.

Compensation / Benefits
  • time off programs
  • medical coverage
  • dental coverage
  • vision coverage
  • mental health support
  • paid parental leave
Responsibilities
  • Own and pursue ambitious research and engineering goals aligned with strategic initiatives
  • Develop novel models and technical solutions for large-scale enterprise problems
  • Design, build, and maintain production-ready services, including scalable APIs and agentic evaluators
  • Collaborate with a strike-team of researchers and engineers to deliver complex projects impacting core AI products
Key requirements
  • Ph.D., Master's, or Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
  • Strong publication record in top AI venues or proven track record of shipping AI products
  • Demonstrated expertise in one or more focus areas: LLMs, Agentic Systems, Computer Vision/Multimodal, Speech Intelligence, or Research Engineering
  • Experience with Python and deep learning libraries (e.g., PyTorch, Jax, or DeepSpeed)
  • Proven ability to implement, operate, and deliver results at large scale
  • Outstanding communication
  • Collaborative mindset
  • Problem-solving skills
  • LLMs, Agentic Systems, Computer Vision/Multimodal, Speech Intelligence, Efficient Systems, Core Modeling
  • Python and deep learning libraries (PyTorch, Jax, DeepSpeed)
  • Production cloud deployments (AWS/GCP), Kubernetes, MLOps

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