In this high-impact role, you will operate at the forefront of responsible AI development, working closely with research scientists and engineers in AI Research, as well as cross-functional partners in Responsible AI, Agentforce, and other teams across Salesforce

• You will lead the design and implementation of Trust Layer models, as well as RAI tools and frameworks that ensure our AI systems are fair, accountable, and transparent
• Using advanced machine learning techniques, you’ll generate actionable insights, drive research excellence, and support responsible AI practices across the full development lifecycle—from experimentation to production deployment
• Build state-of-the-art LLM safeguards for enterprise
• Analyze data and models to identify potential trust and safety issues; define testing protocols for different data types and model architectures; recommend mitigation strategies, tooling investments, and safe thresholds for deployment
• Define technical goals and guide research/engineering teams on responsible AI best practices
• Offer development support and thought leadership on critical ethical tradeoffs in algorithmic design
• Contribute to the development and adoption of libraries and tools that support evaluation, testing, and mitigation of risks
• Build features that enhance explainability and user trust in model outputs
• Collaborate with industry leaders in similar positions in peer organizations on ways to improve the state of responsible AI development

Builds trusted relationships across all levels, both internally and externally

• Practical experience in machine learning
• MS or Ph.D. in a quantitative discipline with 3+ years of industrial experience, or a BS in a quantitative discipline with 5+ years of industrial experience
• Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets
• Proficient in using Python and common machine learning frameworks (e.g., TensorFlow, PyTorch) and AI tools to implement models and algorithms
• Up to date on the evolution of trusted AI and ability to meet both state-of-the-art and global standards for evaluation, particularly in generative AI
• Experience working across teams of engineers, data scientists, and researchers
• Strong communication skills
• Comfortable presenting ideas to peers, cross-functional groups, and executives in multiple formats, from slide decks to informal chats
• Thoughtfully challenges the status quo to enhance team productivity, effectiveness, and culture while maintaining strong, positive partnerships
• Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems
• Demonstrated experience with actually shipping code, getting data science into production

Passion for the idea that technology can be a force for social good and for ethics and fairness