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Lead Applied Scientist - Responsible AI
Guides the ethical development and deployment of cutting-edge artificial intelligence products by implementing safety frameworks, bias assessments, and trust protocols across enterprise AI systems
Key Responsibilities:
- Develop strategy alongside AI research, engineering, and product teams to create generative AI capabilities while mitigating ethical risks
- Identify potential negative consequences of AI systems and drive prioritization of mitigations into product roadmaps
- Implement responsible AI processes including bias assessments, accuracy measurements, harms modeling, and privacy protections
- Lead trust and safety initiatives and benchmark AI models against ethical and safety standards
- Conduct applied research on AI alignment, adversarial robustness, interpretability, and fairness in generative AI
- Coordinate with cross-functional teams including design, legal, and product management on AI ethics implementation
- Deliver solutions for real-world, large-scale responsible AI challenges
Skills & Tools:
- AI ethics and safety frameworks (alignment, adversarial robustness, explainability, fairness)
- Machine learning and deep learning research methodologies
- Generative AI safety and evaluation tools
- Programming languages (Python, R, relevant ML frameworks)
- Research publication and academic collaboration experience
- Large-scale AI system implementation and operations
- Cross-functional leadership and project management
- Strong written and verbal communication for technical and non-technical audiences
- Experience with AI safety conferences (NeurIPS, FAccT, AIES)
Where This Role Has Appeared:
- Salesforce (Enterprise Software, Multiple US Cities, $157k-$334k, July 2025)
Variants & Related Titles:
- AI Safety Researcher
- Applied AI Ethics Scientist
- Responsible AI Research Lead
- AI Alignment Researcher
- AI Trust and Safety Scientist
Why This Role Is New:
Lead Applied Scientist for Responsible AI emerged in 2022-2023 as enterprise AI products moved from experimental to production scale and companies realized they needed dedicated research expertise to ensure AI safety and ethics. The role reflects the growing recognition that responsible AI requires specialized research and implementation expertise, not just policy development.
Trend Insight:
As AI systems become more powerful and widespread, tech companies are investing heavily in research-driven approaches to AI safety, creating senior roles that bridge cutting-edge AI research with practical implementation of ethical AI practices at enterprise scale.
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