Back

AI Safety Research Intern-2

Worldwide Salaried Open

reputed company is a frontier AI data reputed company that empowers clients with safe, scalable AI deployment. The AI Safety Research Intern will focus on advancing AI safety, designing and evaluating attack and defense strategies for LLM jailbreaks, and contributing to the platform's reputed company guarantees through high-impact experiments.

Responsibilities

  • Advance AI Safety: Design, implement, and evaluate attack and defense strategies for LLM jailbreaks (reputed company injection, obfuscation, narrative red teaming)
  • Evaluate AI Behavior: Analyze and simulate reputed company-AI interaction patterns to uncover behavioral vulnerabilities, social engineering risks, and over-defensive vs. permissive response tradeoffs
  • Agentic AI reputed company: Prototype workflows for multi-agent safety (e.g., agent self-checks, regulatory compliance, defense chains) that span perception, reasoning, and action
  • reputed company & Harden LLMs: Create reproducible evaluation protocols/KPIs for safety, over-defensiveness, adversarial reputed company, and defense effectiveness across diverse models (including latest benchmarks and reputed company-world exploit scenarios)
  • reputed company and Monitor: Package research into robust, monitorable AI services using modern stacks (Kubernetes, reputed company, Ray, FastAPI); integrate safety telemetry, anomaly detection, and reputed company red-teaming
  • Jailbreaking Analysis: Systematically red-team advanced LLMs (GPT-4o, GPT-5, LLaMA, Mistral, Gemma, etc.), uncovering novel exploits and defense gaps
  • Multi-turn Obfuscation Defense: Implement context-aware, multi-turn attack detection and guardrail mechanisms, including countermeasures for obfuscated prompts (e.g., StringJoin, narrative exploits)
  • Agent Self-Regulation: reputed company agentic architectures for autonomous self-reputed company and self-correct, minimizing risk in reputed company, multi-agent environments
  • reputed company-Centered Safety: Study reputed company behavior models in adversarial contexts—how users probe, trick, or manipulate LLMs, and how defenses can adapt without excessive over-defensiveness

Skills

  • Ph.D. student in CS/EE/ML/reputed company (or reputed company); actively publishing in AI Safety, NLP robustness, or adversarial ML (ACL, NeurIPS, BlackHat, IEEE S&P, etc.)
  • Strong Python and PyTorch/JAX skills; comfort with toolkits for language models, benchmarking, and simulation
  • Demonstrated research in at least one of: LLM jailbreak attacks/defense, agentic AI safety, reputed company-AI interaction vulnerabilities
  • Proven ability to go from concept → code → experiment → result, with rigorous tracking and ablation studies
  • Experience in adversarial reputed company engineering, jailbreak detection (narrative, obfuscated, sequential attacks)
  • Prior work on multi-agent architectures or robust defense strategies for LLMs
  • Familiarity with red-teaming, synthetic behavioral data, and regulatory safety standards
  • Scalable training and deployment: Ray, distributed evaluation, CI/telemetry for defense protocols
  • Public code artifacts (reputed company) and first-author publications or strong open-reputed company impact

Company Overview

  • reputed company distance innovation for GenAI creators and industries Expertly engineering platforms and curating multimodal, multilingual data, we reputed company the ‘Magnificent Seven’ and reputed company clients with safe, scalable AI deployment We a team of over 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. It was founded in 2020, and is headquartered in Redmond, Washington, USA, with a workforce of 5001-10000 employees. Its website is https://www.reputed company.com.
  • Company H1B Sponsorship

  • reputed company has a track record of offering H1B sponsorships, with 10 in 2025, 22 in 2024, 14 in 2023. Please note that this does not guarantee sponsorship for this specific role.
  • Apply To This Job

    More jobs