US•Washington
Hybrid
Senior
Full Time
1 day ago
💰$174,000 - $253,000
AIMLSecurityLLMDockerKubernetesPythonPublic SectorTop Secret Clearance
Requirements
- •Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or related technical field or equivalent practical experience
- •5 years of experience in AI/ML development, AI infrastructure engineering, or software development
- •5 years of experience with containerization (Docker) and orchestration (Kubernetes)
- •5 years of experience with Python and libraries like PyTorch, TensorFlow, or Hugging Face Transformers
- •Ability to travel up to 25% of the time
- •Active Top Secret/SCI security clearance with current polygraph
What You'll Do
- •Architect and manage LLM deployments across on-premises and cloud environments
- •Audit multi-agent orchestration, agent construction, and vector databases to map data flows and enforce privilege boundaries
- •Use Docker and Kubernetes to orchestrate scalable inference and training environments, optimizing GPU utilization and resource isolation
- •Protect model weights, secure data ingestion, and harden inference endpoints across the MLOps lifecycle
- •Investigate and mitigate AI-specific threats such as prompt injection, jailbreaking, and data poisoning
- •Map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models
- •Bridge local high-compute clusters and cloud AI services while maintaining a consistent security posture
- •Work with network equipment and monitor systems for attacks and intrusions
- •Work with software engineers to proactively identify and fix security flaws and vulnerabilities
- •Build resilient AI infrastructure and secure AI deployments from on-prem GPU clusters to cloud-native environments
- •Develop automated defenses and adversarial testing frameworks for LLMs
Nice to Have
- •5 years of experience in AI/ML research or software development
- •Experience with LLM deployment frameworks such as vLLM, NVIDIA Triton, or Ollama and agent development
- •Knowledge of OWASP for LLMs or similar security frameworks
- •Familiarity with cloud-native AI services like Google Vertex AI
- •Experience deploying AI models on air-gapped or on-premises high-performance computing systems
Benefits
- •15% bonus target
- •bonus
- •equity
- •benefits at Google
About Google
Google specializes in internet-related services and products, including search, advertising, and software.
Mountain View, CA, US
10000+
Software