Application Open:
Full-Time
Job Purpose:
The Architect in the Research and Development department at MBZUAI will be responsible for leading the design and development of innovative AI research projects. The ideal candidate will have a deep understanding of AI technologies, architecture design, and programming languages. They will work closely with the research team to ensure that the projects are aligned with the research goals and objectives of the university. The Architect will lead the development of software solutions that meet the highest standards of quality, scalability, and performance. They will also be responsible for mentoring and coaching junior developers to ensure the growth and development of the team.
Key Responsibilities:
- Research and Design
- Conduct in-depth research and analysis to identify innovative architectural solutions for the development and deployment of AI/ML systems.
- Develop conceptual designs and prototypes of AI system architectures that push the boundaries of scalability, efficiency, and robustness.
- Collaborate with interdisciplinary teams, including AI researchers, software engineers, data scientists, and subject matter experts, to integrate cutting-edge AI technologies and methodologies into the system design.
- Stay abreast of the latest trends, technologies, and best practices in the field of AI architecture, including emerging paradigms such as edge computing, federated learning, and trustworthy AI.
- Architectural Visualization and Prototyping
- Create detailed 3D models, renderings, and animations to visualize the proposed architectural designs.
- Construct physical and virtual prototypes to test and refine the design concepts.
- Collaborate with the university’s visualization and simulation teams to integrate advanced technologies, such as virtual reality and augmented reality, into the design process.
- Effectively present and communicate architectural design ideas to stakeholders, including researchers, administrators, and funding agencies.
- Project Management and Coordination
- Manage the architectural design and development process, ensuring timely delivery and adherence to project requirements.
- Monitor and report on the progress of the architectural design projects, identifying and mitigating potential risks or challenges.
- Facilitate regular meetings and communication with the research community to gather feedback and incorporate their insights into the design process.
- Compliance and Regulations
- Ensure that the AI system architectures and designs comply with all relevant data privacy regulations.
- Stay informed about the latest developments in AI-specific regulations and guidelines, particularly those related to research facilities.
- Collaborate with the university’s legal, compliance, and risk management teams to address any regulatory requirements or potential liabilities associated with the AI/ML systems.
- Contribute to the development and implementation of the university’s AI governance framework, including policies, standards, and ethical guidelines for the responsible development and deployment of AI technologies.
Academic Qualification:
- Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
Professional Experience:
- Minimum 7-10 years of experience in designing and developing complex AI/ML systems, with a deep understanding of AI architectures, algorithms, and deployment strategies.
- Proficient in leveraging a wide range of AI/ML frameworks and tools, such as TensorFlow, PyTorch, Keras, and sci-kit-learn.
- Strong understanding of AI concepts, algorithms, and methodologies, with a focus on practical application in research projects
- Hands-on experience in building and optimizing AI models, including computer vision, natural language processing, speech recognition, and predictive analytics.
- Experience in data preprocessing, feature engineering, model training, validation, and deployment in AI projects
- Demonstrated expertise in designing and documenting AI system architectures, including logical and physical components, data flows, and integration points.
- Ability to work collaboratively with cross-functional teams, including data scientists, software engineers, and domain experts, to define and implement AI/ML solutions.
Preferred:
- Masters in AI, Machine Learning, or a relevant discipline is preferred.
- Experience working in research-intensive environments or world-renowned research-based universities known for their AI expertise and innovation.
