Applied NLP Researcher

Overview

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.

RequiredQualifications

Education

• 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).