Key Responsibilities

1. Lead the research of technology for improving efficiency in Computer Vision models while performing target capabilities or supporting many capabilities, such as novel architectures and improved pre-training.
2. Design and implement Computer Vision algorithms for model training and prediction, leverage ML infrastructure, and contribute to model optimization and data processing, using Pytorch or other frameworks.
3. Integrate and improve Computer Vision algorithms to work with other models such as LLMs
4. Identify defined problems/gaps in existing technology and engage other Research teams, stakeholders and leaders to expand efficient Computer Vision technology.
5. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies.
6. Write up results in design documents, technical reports, and papers for publication.
7. Represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.
8. 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 Computer Vision experience.

Minimum Professional Experience

• Experience with state-of-the-art Gen AI techniques and models (e.g., LLMs, Multi-Modal, Large Vision Models) or with Gen AI-related concepts (e.g., language modeling, computer vision).
• Knowledge of algorithms, including one or more of the following: imaging, computer vision, computer graphics, or parallel computation.
• Experience with software development in one or more programming languages (e.g. Python, C++), and with data structures/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

• Knowledge of modern deep learning techniques and Generative AI for photography.
• 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).