Applied NLP Researcher

OriginAI is a leading AI laboratory at the forefront of applied research and high impact defence solutions. Our team of top-tier experts is dedicated to advancing the state of the art in artificial intelligence, with a particular focus on developing intelligent agents and next-generation NLP systems

We are seeking a highly motivated and skilled Applied NLP Researcher to join our NLP team. The successful candidate will play a key role in developing advanced NLP capabilities and contributing to mission-critical systems. Ideal candidates bring a strong academic foundation and a proven ability to translate theoretical insights into practical, robust implementations

We combine a deep commitment to academic advancement, regularly publishing in top-tier venues, with a focus on deploying robust, operational systems that make a tangible impact in the defence domain

Core Responsibilities

The successful candidate will be responsible for a range of tasks centered on modern NLP technologies, including:

Developing and deploying task-specific agents and intelligent conversational systems

Designing and executing experiments for Large Language Model (LLM) training and fine-tuning

Establishing robust evaluation frameworks for new NLP models, agents, and applications

Implementing and optimizing prompt engineering and prompt tuning techniques to maximize model performance

Staying current with the latest research and developments in the field of NLP and Artificial Intelligence

Requirements

Master’s degree in Computer Science, NLP, Machine Learning, or a closely related field (Ph.D. an advantage)

Skills And Experience

Proficiency in programming languages commonly used in NLP (e.g., Python)

Solid understanding of machine learning and deep learning principles, particularly in the context of NLP

Experience with major deep learning frameworks

Proven experience with NLP projects

Preferred Qualifications (Advantage)

Prior applied knowledge and practical experience in developing and deploying NLP models in a production environment

Familiarity with LLM architectures (e.g., Transformers) and techniques

Experience with cloud computing platforms (e.g., AWS, GCP, Azure)

*Only relevant applications will be answered

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