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Large Language Model Architect

30+ days ago 2026/10/22
Other Business Support Services
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Job description

Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Large Language Models (LLMs)
Good to have skills : NA
Minimum 15 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Lead applied AI research and convert emerging advances into production-ready capabilities, reusable intellectual property, and differentiated client offerings.
Expert ability to evaluate and institutionalize emerging tools such as OpenAI Codex, Claude Code, Cursor, GitHub Copilot, Hugging Face, Weights & Biases and LangSmith, selecting them based on experimental rigor, reproducibility, security, cost and production-transfer potential.
Must demonstrate applied research that has materially influenced deployed AI products or platforms. Purely academic leadership or prototype-only experimentation is not sufficient.
Roles & Responsibilities:
- Define the applied research agenda across agentic AI, reasoning, memory, evaluation, multimodal systems, and enterprise AI.
- Select high-value research problems aligned with business and client priorities.
- Lead rapid experimentation with clear transition criteria from research to engineering.
- Build reusable algorithms, frameworks, benchmarks, and reference architectures.
- Partner with engineering teams to productionize validated research.
- Establish reproducibility, security, responsible AI, and research-quality standards.
- Build external thought leadership through patents, publications, partnerships, and open source where appropriate.
Professional & Technical Skills:
- Modern machine learning, foundation models, agentic systems, and evaluation.
- Track record of converting research into scalable production systems.
- Model behavior analysis, experimental validity, latency, cost, robustness, and feasibility.
- Leadership of senior researchers and engineers.
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