Conduct original research on large language models and multimodal architectures, focusing on scalable design, cross:
modal alignment, and model behavior foundations.
:
Develop advanced techniques for efficient training and inference, including optimization of pipelines, distributed serving, and latency:
aware system design.
:
Innovate in numerical computing for AI, such as precision optimization, high:
performance tensor algorithms, and new approaches to accelerating large:
scale computation.
:
Pioneer methods for Agentic AI, including autonomous task decomposition, tool:
use frameworks, and multi:
agent coordination strategies.
:
Demonstrate a strong research track record with 5+ top:
tier AI publications, and preferably distinctions such as ICPC/IMO awards, outstanding paper or best paper recognitions at major conferences
Focus Areas
:
LLM and Multimodal Models:
Architecture design, cross:
modal alignment, and scalable model orchestration.
:
Training and Inference:
Optimization of training pipelines, distributed inference, and latency:
efficient serving.
:
Numerical Computing:
High:
performance tensor operations, precision management, and algorithmic acceleration.
:
Agentic AI:
Autonomous task decomposition, tool:
use integration, and multi:
agent coordination.
Requirements
:
Ph.D.
or equivalent experience in Computer Science, Electrical Engineering, or related fields with a focus on large:
scale AI models or intelligent systems.
:
Strong background in LLMs/multimodal models, training and inference optimization, numerical computing, or agentic AI frameworks.
:
Proven ability to produce impactful research, evidenced by publications in top:
tier AI venues or equivalent high:
impact contributions.
:
Experience with large:
scale model training, multimodal systems, or advanced AI runtime/serving platforms preferred.
:
Fluent in English; proficiency in French is a plus. microTECHGlobal Ltd Information Technology CDI market rate