Research Scientist – NLP

Application open:

Full-time

Job purpose:

As a research scientist specializing in natural language processing (NLP) with a focus on large language models and deep learning, your role will be crucial in advancing cutting-edge language processing technologies and contributing to the development of intelligent systems. You will be responsible for a wide range of tasks encompassing research, development, and implementation of NLP solutions, with a particular emphasis on Python coding, machine learning techniques, and deep learning methodologies.

Key responsibilities:

Lead the research of technology for improving the efficiency of large language models (LLM) while performing target capabilities or supporting many capabilities, such as novel architectures and improved pre-training.

Design and implement NLP algorithms for model training and prediction, leverage ML infrastructure, and contribute to model optimization and data processing, using PyTorch or other frameworks.

Integrate and improve LLM algorithms to work with other models such as computer vision models.

Identify defined problems or gaps in existing technology and engage other research teams, stakeholders, and leaders to expand efficient LLM technology.

Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies.

Write up results in design documents, technical reports, and papers for publication.

Represent the institution at industry conferences and events, showcasing cutting-edge HPC and deep learning capabilities and establishing it as a global leader in AI research and innovation.

Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.

Academic qualifications:

Minimum

Master’s in computer science, a related technical field, or equivalent practical experience.

Preferred

PhD or equivalent research experience in natural language processing.

Minimum professional experience:

Experience with state-of-the-art generative AI techniques and models (e.g., LLMs, multi-modal, large vision models) or with generative AI-related concepts (e.g., language modeling, computer vision).

Experience with software development in one or more programming languages (e.g., Python, C++), and with data structures and algorithms.

Excellent problem-solving and troubleshooting skills to address complex technical challenges.

Effective communication and collaboration skills to work with cross-functional teams.

Ability to effectively navigate ambiguity.

Preferred professional experience:

Experience leading research efforts and influencing other researchers.

Experience with efficiency, modularity, or related topics for LLMs.

Experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Experience with design and optimization of algorithms in performance-constrained environments (e.g., mobile).

Experience in innovative research, contributing to research communities including publishing in forums (e.g., ACL, EMNLP, NAACL, EACL, COLING, ICLR, AAAI, NeurIPS).