AI Architect
Tasks
- Build low latency inference and feature serving
- Build production AI ML pipelines
- Conduct A/B testing and statistical validation
- Deploy and monitor models for performance drift
- Deploy generative AI solutions and large language models
- Design end to end machine learning and AI systems
- Develop APIs using modern Python frameworks
- Develop responsible AI metrics and benchmarks
- Develop, train, and validate machine learning models
- Ensure fairness explainability and regulatory compliance
- Implement AI guardrails safety frameworks and compliance controls
- Implement MLOps and model versioning
- Implement model monitoring dashboards governance and retirement
- Prepare documentation and technical specifications
- Translate business problems into AI ML opportunities
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AIOps | AWS | Adversarial Attacks | Agentic Systems | Azure | B testing | Big Data | Cloud platform | Deep learning | Differential Privacy | Embeddings | Encryption | Ensemble Methods | Explainable AI | Fairness metrics | FastAPI | Feature serving | Fine Tuning | Google Cloud | Google Cloud Platform | Langchain | Langgraph | Language Models | Large Language Models | Low Latency | Low Latency Inference | MLOps | Machine Learning | Model Governance | Model Monitoring | Model Reproducibility | Model Serving | Model versioning | Multi-cloud | Online prediction | Prompt engineering | Python | RAG | Retrieval-Augmented Generation | Secure Model Serving | Semantic Search | Statistical validation | Streaming Data | Transfer Learning | Vector Databases
Education
N/A
Roles
AI | AI Architect | Architect | Engineer | Learning Engineer | Machine Learning Engineer
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