Adversarial Machine Learning Engineer at C-Serv

Boise, Idaho, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Jul, 26

Salary

0.0

Posted On

21 Apr, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Adversarial Machine Learning, AI Security, LLM Systems, Python, Prompt Injection, Jailbreaking, Data Exfiltration, Model Inversion, RAG Architectures, Vector Databases, Model Fine-tuning, API Security, Penetration Testing, OWASP LLM Top 10, Attack Simulation

Industry

Business Consulting and Services

Description

The Opportunity We are building a dedicated AI Red Team to rigorously test and harden enterprise-scale AI products. We are looking for an adversarial machine learning specialist who thinks like an attacker. This role focuses on identifying vulnerabilities in LLM-driven systems, breaking model guardrails, exploiting data pathways, and stress-testing AI deployments before they reach enterprise customers. This is a hands-on technical role at the core of AI security. What You’ll Do Conduct adversarial testing across LLM and AI-based systems Execute real-world attack simulations, including: Prompt injection Jailbreaking and guardrail bypass Data exfiltration attempts Model inversion and evasion techniques RAG manipulation Develop scripts and tooling to automate attack scenarios Analyse model behaviour under adversarial pressure Identify systemic vulnerabilities in: APIs Embedding pipelines Vector databases Fine-tuned model implementations Collaborate with engineering teams to validate remediation Document findings clearly and concisely You will help ensure AI systems are resilient before they are deployed at scale. What We’re Looking For Core Technical Skills Strong experience in adversarial ML or AI security research Experience working with LLM-based systems (OpenAI, Anthropic, open-source models, etc.) Deep understanding of: Prompt injection techniques Model jailbreak methodologies AI system exploitation vectors Strong Python skills Experience building custom attack tooling or experimentation frameworks AI Systems Knowledge Familiarity with: RAG architectures Vector databases Model fine-tuning workflows API-based model deployments Understanding of model safety mechanisms and guardrails Nice to Have Background in cybersecurity or penetration testing Familiarity with OWASP LLM Top 10 Experience working in enterprise environments Who You Are Curious and relentless Comfortable thinking like an attacker Creative in finding non-obvious vulnerabilities Detail-oriented but fast-moving Comfortable operating in ambiguity Independent but collaborative You don’t just run test cases — you design new ones. Comprehensive Private Medical Coverage Support for Mental Health Expenses Life Insurance Options Attractive Compensation Package

Responsibilities

Conduct adversarial testing on LLM-driven systems to identify vulnerabilities such as prompt injection and jailbreaking. Develop automated attack scripts and collaborate with engineering teams to validate remediation efforts.