C-Serv

Adversarial Machine Learning Engineer

🇨🇦 Calgary, Kanada Hybrydowo IT Senior Opublikowano Maj 19, 2026
Lokalizacja Calgary, Kanada
Tryb pracy Hybrydowo
Poziom doświadczenia Senior
Kategoria IT
Kategoria IT Inżynier bezpieczeństwa
Język English
Opublikowano 19 maja 2026
Ostatnio sprawdzono 31 maja 2026
Kontekst JobGrid

Podsumowanie roli od JobGrid

Adversarial Machine Learning Engineer at C-Serv: Calgary, Kanada; Hybrydowo; Senior; IT; Inżynier bezpieczeństwa. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.

  • Location and workplace: Calgary, Kanada, Hybrydowo
  • Role classification: IT, Inżynier bezpieczeństwa, Senior
  • Source freshness: checked by JobGrid on 2026-05-31.
  • Application path: candidates continue to the employer application page with non-personal referral tags.

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.