Senior Applied Scientist - Responsible AI

Salesforce.com, Inc.•New York, NY

37d

About The Position

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's Office of Ethical and Humane Use is hiring an Applied Responsible AI Research Scientist to play a pivotal role in guiding the responsible development of cutting-edge artificial intelligence products. Working together with the Responsible AI & Tech team and in close partnership with both Salesforce AI Research and Frontier AI teams, they will deliver guidance, guardrails, and features that ensure the next generation of AI is designed, developed, and delivered in alignment with Salesforce's ethical use and responsible AI principles. The ideal candidate will have experience in artificial intelligence and specifically the field of responsible / ethical AI including Generative AI. They will work across teams to implement responsible AI processes including but not limited to bias assessments, accuracy measurements, harms modeling, privacy (memorization, unlearning), security, and AI model trust and safety.

Requirements

Master's degree (or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Data Science, Social or Applied Sciences, or a related field
5-8 years of relevant experience in AI ethics, AI research, Security, Trust & Safety, or similar roles. Additional experience researching responsible generative AI challenges and risk mitigations.
Expertise in one of the following areas: alignment, adversarial robustness, interpretability/explainability, or fairness in generative AI.
Proven leadership, organizational, and execution skills. Passion for developing cutting-edge AI ethics technology and deploying it through a multi-stakeholder approach.
Experience working in a technical environment with a broad, cross-functional team to drive results, define product requirements, coordinate resources from other groups (design, legal, etc.), and guide the team through key milestones
Proven ability to implement, operate, and deliver results via innovation at a large scale.
Excellent written and oral communication skills, as well as interpersonal skills, including the ability to articulate technical concepts to both technical and non-technical audiences.

Nice To Haves

8-10 years of relevant experience in AI ethics, AI research, security, Trust & Safety, or similar roles
Advanced degree in Computer Science, Human-Computer Interaction, Engineering, Data Science or quantitative Social Sciences
Published research on algorithmic fairness, accountability, and transparency, especially around detecting and mitigating bias or AI safety.
Full-time industry experience in deep learning research/product.
Strong experience building and applying machine learning models for business applications.
Strong programming skills
Experience in implementing high-performance and large-scale deep learning systems.
Thoughtful about AI impacts and ethics.
Fantastic problem solver; ability to solve problems the world has not solved before.
Presented a paper at NeurIPS, FAccT, AIES, or similar conferences
Works well under pressure, and is comfortable working in a fast-paced, ever-changing environment.

Responsibilities

Develop strategy, alongside Salesforce AI Research, engineering, data science, and product management to create, develop, and ship cutting-edge generative AI capabilities for Salesforce customers while mitigating ethical risks and capturing ethical opportunities.
Identify potential negative consequences, then identify how those consequences might be mitigated and drive prioritization of those mitigations into a team's roadmap. Conversely, identify positive ethical impacts in a roadmap/specification/design and ways to amplify them in the product.
Trust and safety, as well as CRM benchmarking against other models and different versions of the same model.
Develop solutions for real-world, large-scale problems.
As needed, lead teams to deliver on more complex pure and applied research projects.