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Elloe AI

LLM Red Team Intern, Evaluation Systems (Remote)

Remote Austin, TX
Machine Learning AI GPT-4 Claude Gemini
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Description

LLM Red Team Intern (Evaluation Systems)

Location: Austin, Texas

Department: Engineering

Location Type: REMOTE

Employment Type: INTERN

Internship | Remote | LLM Evaluation | Reports to CTO or Safety Lead

About Elloe
Elloe is the immune system for AI.
We don’t train models — we protect their outputs. We trace every hallucination, enforce every policy boundary, and create an audit trail for every critical LLM interaction.

Our modules (TruthChecker™, AutoRAG™, Autopsy™) are embedded in hospitals, banks, and regulatory sandboxes. Our job is to make sure these systems are safe before anything hits production.
This role will help us break, stress-test, and harden the models used by governments and enterprises alike.

About the Role
You’ll red team real-world LLM deployments, design eval harnesses, and help scale Elloe’s output-level safety layer. This isn’t just prompt tuning — it’s forensic risk mapping.
You’ll work directly with product and safety leads to uncover failure patterns and codify guardrails for GenAI systems under real-world scrutiny.

What You’ll Own
1. Red Teaming & Risk Testing
  • Create prompts to trigger hallucinations, policy violations, or failure scenarios
  • Stress test Elloe-protected deployments using open and proprietary models
  • Document behavioral exploits across use cases (healthcare, compliance, gov)
2. Evaluation Design
  • Build truthsets and scoring rubrics tied to factuality, policy, or ethical standards
  • Benchmark Elloe’s modules across model types (Claude, GPT-4, Gemini, open models)
  • Collaborate with product to refine and expand our eval harnesses
3. Safety Intelligence
  • Identify blind spots in current detection logic
  • Recommend scoring methods or red flag thresholds for deployment
  • Support internal model comparison reports or customer safety audits

Who You Are
  • ML/AI researcher or engineer (undergrad, grad, or early career)
  • Experience working with LLMs, eval sets, and prompt design
  • Strong attention to detail, grounded in safety and adversarial thinking
  • Bonus: exposure to safety benchmarks like TruthfulQA, MMLU, or red teaming tools

Why This Matters
This is real-world alignment, not research theater.
You’ll be helping define how AI gets deployed responsibly — with traceability, transparency, and real-time protection.

You’ll leave this role with:
  • Exposure to high-stakes LLM safety deployments
  • Published frameworks or scoring methods used by enterprises
  • Mentorship from technical founders operating at the bleeding edge of AI safety

Logistics & Application
  • Start Date: Rolling
  • Duration: 12–16 weeks
  • Compensation: Research stipend
  • Location: Remote-first; flexible for global candidates
  • To Apply: Share a jailbreak or eval idea you’d love to run against GPT-4.
Elloe AI
Elloe AI

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