NLP Engineer

We are seeking an experienced NLP and LLM Engineer to join our innovative team. The ideal candidate will have a strong background in natural language processing, machine learning, and deep learning, with a specific focus on developing and optimising large language models. You will be responsible for designing, building, and deploying advanced NLP solutions to solve complex real-world problems.
Responsibilities:
Design, develop, and fine-tune large language models (LLMs) to enhance their performance on specific tasks such as question answering, summarization, and instruction tuning.
Implement Retrieval-Augmented Generation (RAG) techniques to improve model responses using external knowledge sources.
Apply Reinforcement Learning from Human Feedback (RLHF) to refine model outputs and ensure alignment with user preferences.
Conduct research and development on transformer architectures, attention mechanisms, and other state-of-the-art NLP methodologies.
Develop and optimise models for tasks such as text classification, summarisation, entity recognition, sentiment analysis, and machine translation.
Collect, preprocess, and analyse large datasets for training and evaluating NLP models.
Utilise vector databases to manage and retrieve high-dimensional data efficiently.
Implement data augmentation techniques to enhance training datasets and improve model robustness.
Deploy NLP models into production environments, ensuring scalability and robustness.
Monitor and maintain deployed models, making improvements as needed based on performance metrics and user feedback.
Develop and maintain APIs and microservices for integrating NLP models into applications.
Stay up-to-date with the latest research in NLP and machine learning.
Experiment with advanced techniques like instruction tuning to improve model performance on specific tasks.
Contribute to the research community through publications, presentations, and participation in relevant conferences.
Explore and implement techniques like zero-shot, few-shot learning, and transfer learning to enhance model adaptability.
Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate NLP solutions into products and services.
Collaborate with the engineering team to develop scalable solutions for complex NLP challenges.
Requirements:
Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
5-10 years of professional experience in NLP and machine learning.
Proven track record of developing and deploying large language models and NLP applications.
Proficiency in programming languages such as Python, Java, or C++.
Strong proficiency in Python and experience with machine learning libraries such as Tensor Flow, PyTorch, and scikit-learn.
Experience with NLP frameworks and libraries (e. g., Tensor Flow, PyTorch, and Hugging Face Transformers).
Strong understanding of machine learning algorithms, deep learning, and statistical methods.
Hands-on experience with RAG, RLHF, and instruction tuning.
Knowledge of vector databases (e. g. Pinecone) and their integration into NLP workflows.
Familiarity with cloud platforms (e. g., AWS, Google Cloud, Azure) and containerization technologies (e. g., Docker, Kubernetes).
Experience with tools and platforms like GPT, BERT, T5 and other transformer-based models.
Understanding of prompt engineering and its applications in LLMs.
Strong problem-solving skills and the ability to think creatively.
Excellent communication and teamwork abilities.
Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:
Experience with unsupervised learning techniques and semi-supervised learning.
Familiarity with reinforcement learning and its applications in NLP.
Contributions to open-source NLP projects.
Experience with multilingual NLP models and techniques.
Understanding of ethical considerations and bias mitigation in NLP.

Experience
5-9 yrs