Lead/Principal Responsible AI Research Scientist

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About Salesforce

We're Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too - driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good - you've come to the right place.

Salesforce AI Research is seeking a forward-thinking and accomplished researcher 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 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 Salesforce AI Research team https://www.salesforceairesearch.com

Job Responsibilities:

• 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.

Minimum Qualifications:

• Practical experience in machine learning

• MS or Ph.D. in a quantitative discipline with 8+ years of experience or a BS in a quantitative discipline with 10+ years of 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 (e.g., cursor, W&B, huggingface) to implement models and algorithms.

• Proficient in SQL, shell scripting, and Unix/Linux command-line tools.

• 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.

• Earns trust in relationships both internally and externally, and at all levels of the organization. Challenges the status quo to improve the productivity, effectiveness, and culture of a team - without burning bridges.

• Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems.

• Demonstrated experience with actually shipping code, getting data science into production

• Ability to stay abreast of the latest findings in the field, new technologies, and best practices

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

Preferred Qualifications:

• 10+ years of business experience

• Experience with designing and building micro-services, familiar with Kubernetes/containerization/RESTful API/gRPC, etc.

• Strong experience leading multi-disciplinary teams driving significant business results

• Knowledge of enterprise SaaS space

• Strong publications at top AI conferences

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Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.