Sr.Security ML / AI Engineer
Tasks
- Build model evaluation frameworks
- Build training data pipelines
- Collaborate on multi agent agent architecture
- Deploy and manage model inference endpoints
- Design model routing layer
- Design prompt engineering patterns
- Fine tune models for alert triage risk scoring and classification
- Implement analyst feedback loop
- Implement dashboard signals for retraining
- Implement token usage monitoring
- Monitor models for drift and accuracy degradation
Perks/Benefits
- 401k matching
- Comprehensive health care
- Dependent care FSA
- Health care FSA
- Health savings account
- Lease vehicle program
- Paid Holidays
- Paid time off
- Referral services
- Relocation assistance
- Tuition reimbursement
- Vehicle purchase discount
- Workplace flexibility
Skills/Tech-stack
A/B | A/B Testing | AWS SageMaker | Agentic AI | Artificial Intelligence | Attention Mechanisms | B testing | CI/CD | Caching | Chain-of-Thought | Container Serving | Evaluation Pipelines | F1-score | False Positive | False Positive Rate | Fine Tuning | Huggingface | Hyperparameter Tuning | Inference Server | Inference endpoints | Knowledge Distillation | LLM Fine-tuning | Language Models | Large Language Models | LoRA | Machine Learning | Mixture of Experts | Model Drift | Model Registry | Monitoring | PEFT | Precisión | Prompt engineering | PyTorch | Python | QLoRA | Quantization | RAG | Recall | TensorRT | Tool use | Transformers | Triton Inference | Triton Inference Server | VLLM | Vector Databases | Vector Search
Education
N/A
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