The AI Engineer deliver high-quality outcomes in a fast-paced environment. The role will design and implement robust, efficient deep learning (DL) techniques, contribute to open-source projects, and develop AI applications. This role involves working at the cutting-edge of Deep Learning, Machine Learning, and Software Engineering. Additionally, the role will lead AI projects, optimize distributed training, job scheduling, and hyperparameter tuning for large DL/CV/NLP models, and improve system efficiency and performance. Collaborating with system architects, team leaders, and engineers, you will build innovative products focused on accuracy, interpretability, and scalability. You will own tasks with measurable results, aligning timelines for rapid performance evaluation. This role is an opportunity to innovate and drive impactful AI solutions for MBZUAI.

Key responsibilities:

Innovation and Development:

• Work at the cutting-edge of Deep Learning, Machine Learning, and Software Engineering, leveraging a diverse range of skills to drive innovation.
• Contribute high-quality code and lead initiatives in developing AI projects and applications.
• Continuously improve the efficiency, robustness, and cost-effectiveness of existing modules and applications through distributed training, job scheduling, and hyperparameter tuning for large DL/CV/NLP models and multi-stage pipelines.

Collaboration and Product Development:

• Collaborate closely with system architects, team leaders, technical product managers, and engineers to build innovative products with a focus on accuracy, interpretability, and performance of machine learning systems.
• Work together with cross-functional teams to align technical solutions with business goals and user needs.

Ownership and Execution:

• Define and own tasks with measurable outcomes, ensuring alignment with team leaders for rapid evaluation of performance efficiency.
• Design and implement scalable, high-performance solutions for training and deploying machine learning models.

Optimization and Troubleshooting:

• Optimize data pipelines and workflows to ensure seamless data ingestion, processing, and model training.
• Troubleshoot and resolve technical challenges related to machine learning systems and infrastructure.

Technical Leadership and Mentorship:

• Mentor junior team members and promote best practices in software engineering and machine learning.
• Drive innovation by experimenting with new algorithms, tools, and frameworks to improve model performance and scalability.

Monitoring and Documentation:

• Ensure robust monitoring, logging, and alerting mechanisms for machine learning systems in production.
• Document technical processes, architectures, and decisions to ensure knowledge sharing and maintainability.

Continuous Learning and Improvement:

• Stay updated with the latest advancements in AI/ML technologies and integrate them into existing workflows.
• Continuously evaluate and adopt new tools and methodologies to enhance system performance and efficiency.

Other Duties:

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