Research Engineer - NLP

Roles & Responsibilities:

• 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.

Required skills:

• 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: Atleast 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 , with a strong ability to design and implement solutions.
• Strong communication and collaboration skills , with the ability to effectively communicate technical research and ideas to both technical and non-technical stakeholders.