Software Engineering Architect
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Job Description
Principal Scientist developing session-based recommendation algorithms and behavioral embeddings. Advancing Salesforce’s internal AI platform powering real-time recommendations and enterprise personalization.
Responsibilities:
- Lead scientific research and development of core algorithms supporting real-time recommendation services such as SessionFlow
- Design and train high-dimensional vector embeddings to capture behavioral signals from raw event streams
- Translate mathematical concepts into production-grade embedding architectures and statistical validation frameworks
- Develop validation dashboards and exploratory data analysis tools to ensure algorithmic output integrity and quality
- Apply state-of-the-art research in representation learning, sequential recommendations, and neural architectures to enterprise problems
- Serve as a primary scientific authority through peer review and architectural guidance on complex modeling decisions
- Build internal machine learning and AI platform capabilities for Salesforce products and personalization
Requirements:
- PhD in Computer Science, Mathematics, Statistics, or a closely related quantitative field
- 15+ years of experience in algorithmic research, statistical modeling, and applied machine learning
- Deep expertise in representation learning, vector embeddings, and sequential/session-based recommendation models
- Advanced proficiency in Python, PyTorch, and scientific computing libraries including NumPy, SciPy, and Pandas
- Strong portfolio of translating theoretical ML research into practical, scalable production systems
- Exceptional analytical skills with a proven ability to debug complex mathematical and algorithmic anomalies in high-volume data streams
Benefits:
- Salesforce benefits and resources supporting balance and wellbeing
- AI agents to accelerate employee impact
- Equal opportunity and non-discrimination policies
- Reasonable accommodation support during application and recruiting
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