Senior Applied Scientist, AI Security

About This Role

Lead the development of secure AI/ML-based solutions for Uber's user-facing products and internal systems. Focus on building robust defense mechanisms protecting the entire AI lifecycle, ensuring model integrity, preventing data leakage, and enabling safe business velocity.

Responsibilities

• Lead efforts to develop and evaluate security controls for large-scale machine learning models
• Harden retrieval-augmented generation (RAG) systems
• Alignment-tune large language models (LLMs)
• Secure agentic workflows across internal and external boundaries
• Develop and evaluate large-scale machine learning model systems in production with a focus on adversarial robustness, input validation, and output sanitization
• Propose, design, and analyze large-scale online experiments to test safety guardrails and detect ecosystem vulnerabilities
• Define and implement metrics to measure security posture, attack surface reduction, and product performance
• Present findings on AI risks, red-teaming results, and mitigations to business and executive audiences
• Collaborate with engineers and product managers to implement secure-by-design ideas and plan future roadmaps
• Optimize and secure retrieval-augmented generation (RAG) systems against prompt injection, indirect injection, and data exfiltration

Requirements

• Ph.D., MS or Bachelors degree in Statistics, Economics, Operations Research, Computer Science, Engineering, or other quantitative field
• Minimum of 2+ years of industry experience as an Applied Scientist or equivalent (if Ph.D or M.S. degree)
• Knowledge of underlying mathematical foundations of machine learning, statistics, optimization, economics, and analytics
• Hands-on experience building and deploying ML models
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis and testing, and model development
• Ability to use a language like Python or R to work efficiently at scale with large data sets
• Proficiency in technologies in one or more of the following: SQL, Spark, Hadoop

Qualifications

• Ph.D., MS or Bachelors degree in Statistics, Economics, Operations Research, Computer Science, Engineering, or other quantitative field
• Minimum of 2+ years of industry experience as an Applied Scientist or equivalent (with Ph.D or M.S. degree); 5+ years of industry experience as an Applied Scientist or equivalent (preferred)

Nice to Have

• Knowledge in modern machine learning techniques applicable to AI Security, Adversarial ML (AML), and model robustness
• Advanced understanding of statistics, causal inference, and machine learning
• 5+ years of industry experience as an Applied Scientist or equivalent
• Experience designing and analyzing large scale online experiments
• Experience working with large scale data sets using technologies like Hive, Presto, and Spark
• Experience with synthetic data generation for red-teaming and adversarial training
• Proficiency in fine-tuning and optimizing large language models (LLMs) for safety (e.g., RLHF, DPO)
• Experience in securing retrieval-augmented generation (RAG) systems
• Familiarity with secure agentic workflows, sandboxing, and their applications in internal and external AI systems

Skills

* Required skills

Benefits