NLP & Generative AI Specialist
Focus: LLM Architectures & Multilingual Text Intelligence
Role Overview
We are seeking a highly skilled NLP & Generative AI Specialist to design and implement advanced language intelligence systems powered by LLMs and modern Generative AI architectures. This role focuses on building scalable AI solutions for multilingual text understanding, retrieval-augmented generation (RAG), and enterprise AI applications.
The ideal candidate combines deep expertise in deep learning frameworks, modern transformer architectures, and multilingual NLP systems, with hands-on experience developing production-grade GenAI pipelines and LLM-powered applications.
Key Responsibilities
- Design and develop advanced LLM architectures and generative AI solutions for complex language intelligence applications.
- Architect and implement Retrieval-Augmented Generation (RAG) pipelines using frameworks such as LangChain and LlamaIndex.
- Build scalable vector-based retrieval systems using vector databases such as FAISS or Weaviate.
- Develop and optimize multilingual NLP models, including machine translation systems and cross-lingual language understanding.
- Evaluate language models and translation systems using industry-standard metrics such as BLEU, COMET, and related evaluation frameworks.
- Fine-tune and deploy transformer-based models for enterprise use cases using Hugging Face and related ecosystems.
- Integrate AI capabilities into applications using Azure OpenAI APIs and modern AI service frameworks.
- Collaborate with cross-functional teams including product, data engineering, and platform teams to deliver production-ready AI systems.
- Stay current with advances in LLMs, transformer architectures, and generative AI research, and apply them to real-world problems.
Required Qualifications
- Deep expertise in deep learning frameworks such as PyTorch or TensorFlow.
- Strong understanding of transformer architectures, attention mechanisms, and modern LLM design patterns.
- Hands-on experience building RAG pipelines and LLM-based applications.
- Experience working with vector databases such as FAISS, Weaviate, or similar retrieval systems.
- Strong programming skills in Python and familiarity with modern ML tooling.
- Experience working with Azure OpenAI or similar LLM platforms.
Preferred Qualifications
- Experience developing multilingual NLP systems, including machine translation and cross-lingual models.
- Familiarity with evaluation metrics and benchmarking for language models and translation systems.
- Experience deploying and scaling LLM applications in production environments.
- Contributions to open-source AI/NLP projects or published research in NLP/GenAI.
- Experience working with large-scale text datasets and distributed model training.
