Software Engineering Architect

About the Team:
Digital Enterprise Technology (DET) at Salesforce builds the internal engines that power our business. The Machine Learning & Innovation (MLI) team is the applied science and infrastructure strike-force responsible for "Foundry," our unified ML/AI Platform. We operate as "Customer Zero," building the high-velocity, real-time streaming feature platforms and recommendation models that power internal products like the Events App and enterprise-wide personalization.
Role Overview:
As a Principal Applied Scientist, you will specialize in advanced statistical testing methodologies, model observability, and exploratory intent detection. You will tackle high-difficulty algorithmic bottlenecks and build the frameworks that ensure our online systems remain accurate, unbiased, and performant as they scale. Your research will directly shape upcoming agentic workflows and next-best-action discovery platforms.
What You'll Do:
Establish comprehensive model observability frameworks to detect data drift, concept drift, and performance degradation in real-time online systems.
Lead exploratory algorithmic research on intent detection and contextual classification for the Next Best Offer (NBO) discovery program.
Design and implement rigorous statistical validation engines to ensure the mathematical integrity of ML models pre- and post-deployment.
Contribute core statistical algorithms and testing methodologies to the enterprise Stats Engine.
Diagnose complex behavioral anomalies in production ML systems using advanced statistical analysis.
Collaborate closely with data engineers and platform architects to ensure telemetry schemas support rigorous scientific evaluation.
What You Bring:
PhD in Computer Science, Applied Mathematics, Physics, or a related quantitative discipline.
15+ years of experience in applied science, statistical modeling, and deep algorithmic problem solving.
Expertise in anomaly detection, model monitoring/observability, and statistical hypothesis testing.
Strong background in Natural Language Processing (NLP) or intent detection methodologies.
Proficiency in Python and advanced data science tooling.
A demonstrated ability to pivot between deep theoretical research and pragmatic, production-focused engineering solutions.

Employment type
Full time