Artificial Intelligence Architect Synkcode

3.0 - 8.0 years

10 - 20 Lacs

pune, chennai, bengaluru

Hybrid

We are seeking an experienced Artificial Intelligence Architect with proven expertise in large-scale language models, specifically Metas LLaMA 3 . The ideal candidate will lead the design, development, and deployment of advanced AI systems, ensuring high performance, scalability, and integration within enterprise or government environments. This role requires a deep understanding of LLM architectures , distributed training , and AI system integration across diverse platforms. Role & responsibilities Key Responsibilities AI Architecture & Strategy Design and implement enterprise-scale AI architectures leveraging LLaMA 3 and other foundation models. Define end-to-end architecture for LLM-powered applications , including inference, fine-tuning, and deployment pipelines. Establish best practices for model governance, monitoring, and compliance . Model Development & Customization Lead the fine-tuning and instruction-alignment of LLaMA 3 for domain-specific use cases (e.g., finance, customs, healthcare, logistics). Optimize model performance through parameter-efficient fine-tuning (PEFT), quantization, pruning, and RLHF (Reinforcement Learning with Human Feedback) . Integrate vector databases, retrieval-augmented generation (RAG) , and multi-modal extensions. Infrastructure & Deployment Architect and oversee distributed training on GPU/TPU clusters. Deploy scalable inference systems with low-latency APIs, containerized environments, and orchestration tools (Kubernetes, Docker, Ray, etc.) . Implement AI DevOps (MLOps) practices for continuous integration and delivery of models. Cross-Functional Leadership Collaborate with data scientists, ML engineers, and software teams to align AI solutions with organizational goals. Mentor AI engineers in LLM fine-tuning, prompt engineering, and model evaluation . Communicate technical architecture to executives and non-technical stakeholders Preferred candidate profile Preferred Skills Experience with agentic AI systems and multi-agent orchestration . Contributions to open-source AI/LLM projects . Knowledge of blockchain-integrated AI systems (smart contracts, decentralized inference). Ability to design real-time AI copilots and autonomous decision-support systems .

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