Senior NLP Research Engineer
1 day ago
Experience:
4-6 Years
Roles And Responsibilities
We're looking for a talented and driven Senior NLP Research Engineer to join our AI/ML team. In this role, you'll design and implement advanced natural language processing models that interpret metadata and user queries across complex video datasets. You'll also contribute to the development of Generative AI-based assistants, integrated into our video management ecosystem, enhancing user experience through natural interaction and smart search.
- Design, develop, Train, fine-tune, and deploy LLM-based NLP models for various enterprise use cases.
- Experience in Designing the network from scratch according to the problem statement given.
- Experience in training methodologies to handle the large dataset to train the networks.
- Collaborate with product, engineering, and data teams to integrate NLP solutions into production-grade systems.
- Build and optimize custom pipelines for document intelligence, question answering, summarization, and conversational AI.
- Experience and understanding with state-of-the-art open-source LLMs (e.g.,GPT, LLaMA, Claude, Falcon etc.).
- Implement prompt engineering, retrieval-augmented generation (RAG), and fine-tuning strategies.
- Ensure ethical, safe, and scalable deployment of LLM-based systems..
- Ensure model reliability safeDesign, develop, Train, fine-tune, and deploy LLM-based NLP models for various enterprise use , performance, and compliance using evaluation and monitoring frameworks.
- Stay updated with the latest research in GenAI and NLP, and apply relevant findings to improve current systems.
Job Requirements
- 4–6 years of experience in NLP, Machine Learning, or Deep Learning roles.
- Proven experience in working with VLMs and LLMs in real-world projects.
- Proficiency with tools such as Hugging Face, LangChain,, TensorFlow/PyTorch .
- Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG frameworks (Not required but appreciated).
- Strong programming skills in Python and some experience with ML Ops or cloud platforms (AWS/GCP/Azure).
- Deep understanding of NLP techniques including basics such as NER, text classification, embeddings, tokenization, Transformers , loss functions etc.
- Knowledge of distributed training and serving of large models.
- Strong problem-solving and communication skills
Skills: llm,ai,deep learning,hugging face,langchain,tensorflow,research,ml,nlp,machine learning,pytorch
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