AI/ML Automation Engineer
Tasks
- Architect AI machine learning capabilities for cybersecurity operations
- Build automation workflows for malware analysis and digital forensics
- Build data ingestion transformation and enrichment pipelines
- Create ML pipelines for training evaluation and deployment
- Create architecture documentation and technical standards
- Deploy containerized AI workloads
- Design autonomous agent workflows
- Develop LLM integrations and RAG solutions
- Develop REST APIs for secure data exchange
- Implement CI CD pipelines for AI model deployment
- Implement cloud native AI solutions on AWS
- Integrate AI decision support into operational workflows
- Provide technical leadership and mentorship
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Amazon Bedrock | CI/CD | ChromaDB | CloudWatch | Databricks | Digital forensics | Docker | ECS | EKS | ETL | Embedding Models | Faiss | FastAPI | Feature Engineering | Generative AI | Git | GitHub Actions | IAM | Incident Response | Jenkins | Kafka | Kinesis | Kubernetes | Lambda | Language Models | Language Processing | Large Language Models | MITRE ATT&CK | MLOps | Machine Learning | Malware analysis | Model Deployment | Model Evaluation | Natural Language | Natural Language Processing | NoSQL | OpenSearch Vector | OpenSearch Vector Engine | Pinecone | Prefect | Prompt engineering | PyTorch | Python | RAG Pipelines | REST APIs | Retrieval-Augmented Generation | S3 | SQL | SageMaker | Scikit-learn | Security Automation | Spark | Streaming Data | TensorFlow | Terraform | Threat Intelligence | Vector Databases | Vector Engine | XGBoost
Education
Roles
AI | AI ML Automation Engineer | Automation Engineer | Engineer
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