Senior Lead Applied Scientist, Responsible AI

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

Job 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.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

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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.

Compensation

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $148,500 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

Key skills/competency

• Machine Learning
• AI Fairness
• Trustworthy AI
• Explainable AI (XAI)
• LLM Safeguards
• Python
• TensorFlow
• PyTorch
• Data Analysis
• Algorithmic Design
• Cross-functional Collaboration