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 ...
Quick apply
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 ...
This role sits at the intersection of adversarial machine learning, enterprise security architecture, and governance. You will lead the design and execution of structured red team engagements across ...
Quick apply
This role sits at the intersection of adversarial machine learning, enterprise security architecture, and governance. You will lead the design and execution of structured red team engagements across ...
This role sits at the intersection of adversarial machine learning, enterprise security architecture, and governance. You will lead the design and execution of structured red team engagements across ...
Quick apply
This role sits at the intersection of adversarial machine learning, enterprise security architecture, and governance. You will lead the design and execution of structured red team engagements across ...
AI Data Engineer Manager
Las Vegas, NV · On-site
... machine learning models and large language models. • Conduct research to provide technical ... adversarial samples. • Help AI product managers and business stakeholders understand the ...
AI Data Engineer Manager
Las Vegas, NV · On-site
... machine learning models and large language models. • Conduct research to provide technical ... adversarial samples. • Help AI product managers and business stakeholders understand the ...
AI Data Engineer - Manager
Las Vegas, NV · On-site
... machine learning models and large language models. • Conduct research to provide technical ... adversarial samples. • Help AI product managers and business stakeholders understand the ...
AI Data Engineer - Manager
Las Vegas, NV · On-site
... machine learning models and large language models. • Conduct research to provide technical ... adversarial samples. • Help AI product managers and business stakeholders understand the ...
AI Data Engineer - Manager
$109.40K - $131.30K/yr
Lead the development of AI models (e.g., machine learning, natural language processing, computer ... Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
AI Data Engineer - Manager
$109.40K - $131.30K/yr
Lead the development of AI models (e.g., machine learning, natural language processing, computer ... Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Lead AI and Data Science Engineer - Manager
$97.90K - $128.90K/yr
Lead the development of AI models (e.g., machine learning, natural language processing, computer ... Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Lead AI and Data Science Engineer - Manager
$97.90K - $128.90K/yr
Lead the development of AI models (e.g., machine learning, natural language processing, computer ... Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Adversarial Machine Learning information
What are the key skills and qualifications needed to thrive as an Adversarial Machine Learning specialist, and why are they important?
To excel in Adversarial Machine Learning, you need a strong background in machine learning, deep learning, statistics, and computer science, typically supported by an advanced degree in a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial attack and defense libraries, and knowledge of security protocols are crucial. Creative problem-solving, critical thinking, and strong communication skills help in designing robust models and explaining complex threats to stakeholders. These competencies are vital to anticipate vulnerabilities, safeguard AI systems, and ensure the reliability of machine learning models in real-world applications.
What are some common challenges faced by professionals working in Adversarial Machine Learning roles?
Adversarial Machine Learning professionals often face the challenge of staying ahead of rapidly evolving attack techniques that can compromise model integrity and security. Managing the balance between model performance and robustness is another key difficulty, as defenses against adversarial attacks can sometimes reduce accuracy or increase computational costs. Collaboration with data scientists, security teams, and software engineers is vital for developing resilient models and implementing effective defenses. Staying current with the latest research and tools is essential for success in this dynamic field.
What is adversarial machine learning?
Adversarial machine learning is a field of study focused on understanding and defending against attacks that manipulate machine learning models by feeding them deceptive input, known as adversarial examples. These attacks can cause models to make incorrect predictions, raising concerns about the security and reliability of AI systems, especially in critical applications like image recognition and autonomous vehicles. Researchers in this area develop techniques to detect, prevent, and mitigate these vulnerabilities to make machine learning systems more robust.
What is the difference between Adversarial Machine Learning vs Data Scientist?
| Aspect | Adversarial Machine Learning | Data Scientist |
|---|---|---|
| Credentials | Knowledge of machine learning, cybersecurity, and threat detection | Degree in data science, statistics, or related fields |
| Work Environment | Research labs, cybersecurity teams, AI development | Business analytics, data analysis, model development |
| Industry Usage | AI security, cybersecurity, machine learning research | Business, finance, healthcare, tech companies |
Adversarial Machine Learning focuses on understanding and defending AI models against malicious inputs, often within cybersecurity contexts. Data Scientists analyze data to extract insights, build models, and support decision-making across various industries. While both roles require machine learning knowledge, Adversarial Machine Learning emphasizes security and robustness, whereas Data Scientists focus on data analysis and predictive modeling.
What are popular job titles related to Adversarial Machine Learning jobs in Nevada? For Adversarial Machine Learning jobs in Nevada, the most frequently searched job titles are:
What job categories do people searching Adversarial Machine Learning jobs in Nevada look for? The top searched job categories for Adversarial Machine Learning jobs in Nevada are:
What cities in Nevada are hiring for Adversarial Machine Learning jobs? Cities in Nevada with the most Adversarial Machine Learning job openings:
Full-time
Medical, Life
Posted 6 days ago
Job 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.
Requirements
What We’re Looking ForCore 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
- Familiarity with:
- RAG architectures
- Vector databases
- Model fine-tuning workflows
- API-based model deployments
- Understanding of model safety mechanisms and guardrails
- Background in cybersecurity or penetration testing
- Familiarity with OWASP LLM Top 10
- Experience working in enterprise environments
- 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.
Benefits
- Comprehensive Private Medical Coverage
- Support for Mental Health Expenses
- Life Insurance Options
- Attractive Compensation Package