Principal AI Researcher

Date PostedJuly 8, 2026LocationNot SpecifiedCompanySalesforceSalary$197,300 - $313,700TypeSenior Level

Job Summary

The Principal AI Researcher at Agentforce Operations will design, implement, and train novel deep learning models on large-scale GPU clusters. This role bridges the gap between cutting-edge research and customer value by developing business intelligence solutions. The position requires strong expertise in transformer architectures, production-grade Python, and distributed systems.

Responsibilities

  • Design and train deep learning models on GPU clusters
  • Prototype new architectures for enterprise data
  • Partner with engineering and product teams to ship production features
  • Stay current with AI research and advise on AI strategy

Required Skills

  • PhD or Master's in CS/Math/Quantitative field
  • Deep understanding of Transformer architectures
  • Production-grade Python and ML frameworks (PyTorch/JAX/TensorFlow)
  • Experience with distributed GPU training
  • Track record of peer-reviewed research

Job Details

What You'll Actually Be Doing - Design, implement, and train novel deep learning models on large-scale GPU clusters. - Prototype new architectures and algorithms for enterprise data, such as tabular, relational, and graph-structured data. - Stay current with AI research, apply relevant breakthroughs, and advise on internal AI strategy - wearing multiple hats as part of a startup-style team that values experimental rigor and shipping well-engineered systems. - Partner with engineering, product, and design teams to turn research into functional, production-ready features that create immediate, tangible customer value. You're Our Person If... - You have a Master's or PhD in Computer Science, Mathematics, or a highly quantitative field with an AI/ML research focus. - You possess experience developing, deploying, and evaluating machine learning models in production or top-tier research environments and have a deep understanding of transformer architectures and advanced retrieval mechanisms. - You design novel, non-standard AI solutions by introducing core architectural changes or applying foundational mathematical disciplines such as stochastic modeling, graph theory, or optimization algorithms, and have a track record of peer-reviewed publications demonstrating this work. - You have production-grade Python skills, including experience with automatic differentiation frameworks like PyTorch, JAX, or TensorFlow, and experience training large-scale models across distributed GPU clusters using frameworks like DeepSpeed or TorchTitan. Even Better If... - You have experience building production-grade ML pipelines using tools like Kubeflow, Airflow, or MLflow for tracking, versioning, and automated retraining. - You've built robust, distributed data pipelines for cleaning and analyzing massive datasets using tools like PySpark.