AI Engineer
Tasks
- Apply NIST and OWASP best practices
- Define AI usage guardrails governance models and compliance policies
- Deploy AI solutions across domains
- Design and execute AI benchmarks
- Design and support LLM deployments
- Develop ROI and cost performance analysis
- Ensure AI system performance reliability and scalability
- Ensure enterprise security and responsible AI adoption
- Evaluate AI platforms and LLMs
- Identify AI strengths limitations and use cases
- Implement AI systems in semiconductor workflows
- Integrate with data lakes and enterprise data platforms
- Optimize resource utilization
- Provide recommendations for AI platform selection and scaling
- Translate engineering use cases into production AI
Perks/Benefits
Skills/Tech-stack
AI Governance | AI Security | API Integration | AWS | Artificial Intelligence | Azure | Benchmarking | Cloud Computing | Cloud platform | Compliance | Data Engineering | Data Lakes | Data Pipelines | Data Processing | Google Cloud | Google Cloud Platform | Hybrid deployment | Language Models | Large Language Models | Large Scale Data | Large-scale | Large-scale Data Processing | Machine Learning | Model Deployment | Model Evaluation | NIST | OWASP | On-prem | On-prem infrastructure | System Integration
Education
N/A
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