Gen AI Architect
Ztek Consulting, Edison, NJ, United States
Experience Required: 15-25 + Years
Must Have Technical/Functional Skills
Mandatory Skills:
1. GenAI Application Development Expertise
Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana
4. Data Engineering for AI Applications
Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
5. AI-Ready Cybersecurity Knowledge
Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools
Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries
6. GenAI Guardrails and Ethics
Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries
Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools
Transparency & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools
Candidate will be working in AI Engineering group, which is collectively responsible for product developments and AI-infused automations.
Candidates need to lead the solution design discussion and arrive at best-in-class architecture by assessing all the pros
and cons across multiple technologies. Build design documentation and implementation.
#J-18808-Ljbffr
Languages & Libraries: Python, Data Engineering, OSS LLMs (Llama2, Mixtral, GPT-Neo, GPT-J)
Tokenization & Frameworks: Tokenizers (SentencePiece, Hugging Face Tokenizers), Fine-tuning Frameworks (Hugging Face Transformers, PyTorch Lightning)
Infrastructure & CI/CD: DevOps, Kubernetes, Docker, Git, Jenkins, GitLab, GitHub Actions
Monitoring & Management: Ray, SeldonCore, MLFlow, MLServer, Triton, BentoML, Prometheus, Grafana
4. Data Engineering for AI Applications
Workflow Automation: Apache Airflow, dbt, Apache NiFi, Fivetran, Airbyte, Great Expectations
5. AI-Ready Cybersecurity Knowledge
Threat Modeling & Security: AI-Specific Threat Modeling Tools, Secure ML Pipeline Tools, API Security Tools
Monitoring & Prevention: AI Security Monitoring Tools, Prompt Injection Prevention Libraries, Adversarial Example Detection Libraries
6. GenAI Guardrails and Ethics
Ethics & Fairness: AI Ethics Frameworks and Tools, Bias Detection and Mitigation Tools, Fairness Metrics Libraries
Privacy & Security: Privacy-Preserving Machine Learning Libraries, Robustness and Security Tools
Transparency & Governance: Model Interpretability Libraries, AI Governance Frameworks and Tools
Candidate will be working in AI Engineering group, which is collectively responsible for product developments and AI-infused automations.
Candidates need to lead the solution design discussion and arrive at best-in-class architecture by assessing all the pros
and cons across multiple technologies. Build design documentation and implementation.
#J-18808-Ljbffr