Principal ML Architect – Security AI & Advanced Model Systems
Tasks
- Build systems for real time security telemetry
- Collaborate on ML infrastructure data pipelines and observability
- Conduct RLHF and RLAIF alignment experiments
- Define tool use reasoning and memory architectures
- Deploy models into enterprise real time environments
- Design AI agents for security workflows
- Design AI security platform architecture
- Develop and fine tune security focused models
- Ensure compliance with SOC2 ISO and GDPR
- Establish evaluation frameworks for detection accuracy and safety
- Integrate agents with SIEM and EDR tools
- Lead next generation LLM systems development
- Optimize inference for low latency high throughput
- Perform model distillation and compression
- Run red teaming and adversarial robustness testing
Perks/Benefits
- Annual wellness days
- Flexible work environment
- Global collaboration
- Recognition programs
- Volunteer days
- Work from anywhere option
Skills/Tech-stack
Adversarial Machine Learning | Anomaly Detection | Batching | Data Loss Prevention | Data loss | Deep learning | DeepSpeed | Distributed Training | EDR | Explainability | FSDP | Feature Engineering | Fine Tuning | Insider Risk | Insider risk detection | Language Models | Large Language Models | Loss prevention | MLOps | Machine Learning | Model Compression | Model Distillation | Pruning | PyTorch | Python | Quantization | RAG | RLAIF | RLHF | Retrieval-Augmented Generation | Risk detection | SIEM | Security telemetry | Threat detection | Transformer
Education
N/A
Regions
Countries
States
Cities
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