Research Engineer - NLP

Research and Development: Design, develop, and implement novel NLP algorithms and models to achieve state-of-the-art performance on various NLP tasks. Algorithm Engineering: Implement NLP algorithms and models from theory to practice, ensuring their scalability, efficiency, and performance. Experimentation and Evaluation: Conduct thorough experiments and evaluations of NLP models to determine their effectiveness and identify areas for improvement. Model Optimization and Deployment: Optimize and deploy NLP models for production-ready use cases, ensuring their reliability and maintainability. Knowledge Sharing and Collaboration: Collaborate with the research team to share knowledge, best practices, and research results. Staying Up-to-Date: Stay current with the latest developments in NLP research and industry trends. Documentation and Communication: Write technical reports, papers, and documentation to communicate research results and best practices. Mentorship and Training: Mentor and train junior researchers and engineers to develop their NLP skills.

Responsibilities

Design, develop, and implement novel NLP algorithms and models; Implement NLP algorithms and models from theory to practice; Conduct thorough experiments and evaluations of NLP models; Optimize and deploy NLP models for production-ready use cases; Collaborate with the research team to share knowledge and results; Stay current with the latest developments in NLP research and industry trends; Write technical reports, papers, and documentation; Mentor and train junior researchers and engineers

Requirements

Strong background in NLP, including language understanding, text processing, and machine learning; Proficiency in one or more programming languages (e.g., Python, Java, C++, R); Familiarity with NLP frameworks and toolkits (e.g., PyTorch, TensorFlow, spaCy, NLTK); GenAI Skills and Tools: RAG, Quantization, LLM-fine tuning, Parameter Efficient Fine-tuning (PEFT) using LoRA/QLoRA, LangChain, LangGraph/AutoGen/CrewAI; MLOps: At least one of MLFlow, DVC, Wandb, Airflow; Strong knowledge of machine learning and deep learning concepts, including supervised and unsupervised learning methods; Research experience with publication(s) in top-tier NLP conferences; Excellent problem-solving and analytical skills; Strong communication and collaboration skills; Ph.D. or M.S. from top Indian institutes (IITs, IIITs, IISc etc.) in Computer Science or a related field; 3-5 years of experience