- Architectural Design : Build scalable, cost-aware systems handling data pipelines, GPU utilization, and model deployment across hybrid or cloud environments.
- Technology &
- Model Selection : Choose between RAG (Retrieval-Augmented Generation) or fine-tuning, and select the best tools (e.g., LangGraph, TensorFlow, PyTorch) for specific use cases.
- System Integration : Guarantee AI solutions integrate seamlessly with existing IT infrastructure and maintain security standards.
- Governance &
- Lifecycle Management : Implement MLOps (ModelOps), monitor for latency and hallucinations, and establish automated guardrails.
- Stakeholder Management : Collaborate with executives, data scientists, and engineers to align technology roadmaps with business ROI.
Key Skills &
- Requirements
- Technical Proficiency : Deep understanding of Large Language Models (LLMs), neural networks, and orchestration frameworks.
- Data Management : Expertise in vector databases, data readiness, and processing large datasets.
- Cloud &
- Infrastructure : Familiarity with major cloud providers (AWS, Azure, GCP) and containerization/orchestration tools (Docker, Kubernetes).
- Leadership &
- Strategy : Exceptional communication and analytical skills to bridge the gap between technical teams and business stakeholders. (ref:hirist.tech)
📌 Interesting Job Opportunity: AI Architect - LLM/Neural Networks (Mumbai)
🏢 Targeticon Digital Services Private
📍 Mumbai
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