Senior/Lead Applied Scientist, Responsible AI

Salesforce•Palo Alto, CA

48d

About The Position

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Salesforce Research advances state-of-the-art AI techniques, developing models and prototypes that pave the path for innovative products at Salesforce. We tackle real-world problems in areas such as image recognition and natural language processing from Salesforce's enterprise customers by harnessing the latest deep learning techniques. As part of our team you’ll learn unique skills, work with talented people and help us shape the future of AI in Palo Alto and our recently announced new hub, Salesforce Research Asia in Singapore! Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Salesforce AI Research is seeking a forward-thinking and accomplished Applied Scientist with deep expertise in AI fairness, accountability, transparency, and explainability (FATE). 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. We’re looking for a principled and collaborative thought leader who is passionate about bridging the gap between innovation and ethical implementation. You will engage with interdisciplinary teams, strategic partners, vendors, and customers while upholding Salesforce’s core values: trust, customer success, equality, innovation, and sustainability. Check out our website to learn more about the Salesforce AI Research team https://www.salesforceairesearch.com

Requirements

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.
Builds trusted relationships across all levels, both internally and externally.
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.

Nice To Haves

Strong experience leading multi-disciplinary teams driving significant business results.
Knowledge of enterprise SaaS space.
Experience with designing and building micro-services, familiar with Kubernetes/containerization/RESTful API/gRPC, etc.
Proficient in SQL, shell scripting, and Unix/Linux command-line tools.
Strong publications at top AI conferences.

Responsibilities

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.