Principal AI Researcher, Agentforce Operations

Join a collaborative, diverse team of researchers at Agentforce Operations. The Foundational Models Team develops the next generation of business intelligence and bridges the gap between cutting-edge research and customer value. Following our recent acquisition, we offer the agility of an early-stage startup backed by the global scale and trust of Salesforce.

- 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 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 designing 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.

- 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.

The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually.