Customer Engineer, Public Sector
Mexico City, CDMX, Mexico
MXN 934K-1300K (estimate) Senior-level Full Time
Tasks
- Architect LLM deployments
- Audit multi agent orchestration and vector databases
- Harden inference endpoints across MLOps lifecycle
- Investigate and mitigate AI threats
- Manage LLM deployments on premises and cloud
- Map testing findings to MITRE ATLAS
- Map testing findings to OWASP for LLMs
- Map testing findings to STRIDE
- Optimize GPU utilization and resource isolation
- Orchestrate scalable inference and training environments
- Protect model weights and secure data ingestion
Perks/Benefits
Skills/Tech-stack
Agent Development | Air-gapped | Air-gapped systems | Cloud Computing | Cloud computing platform | Cloud platform | Computing platform | Data poisoning | Docker | GPU Utilization | Google Cloud | Google Cloud Platform | High Performance | High-Performance Computing | Hugging Face | Hugging Face Transformers | Jailbreaking | Kubernetes | LLM Deployment | Language Models | Large Language Models | Learning operations | MITRE ATLAS | MLOps | Machine Learning | Machine Learning Operations | NVIDIA Triton | OWASP | OWASP for LLMs | Ollama | On premises high performance computing | On-Premises | Performance Computing | Prompt injection | PyTorch | Python | STRIDE | TensorFlow | VLLM | Vector Databases | Vertex AI
Education
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