Job Purpose

As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and
implement innovative machine learning models that address real-world challenges, pushing the boundaries of
artificial intelligence research. You will collaborate with cross-functional teams to deploy scalable solutions,
contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in
the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine
learning models, while supporting the development of transformative AI tools that can influence industries
worldwide.

Key Responsibilities:

• Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.
• Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing,
  pre-training, post-training, evaluation and so on, especially foundation models.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style
  guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates
  and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on
  hardware, network, or service operations and quality.
• Contribute to research papers and 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.
• Perform all other duties as reasonably directed by the line manager that are commensurate with these
  functional objectives.

Academic Qualifications

• Minimum

  Bachelor’s degree or equivalent practical experience.

• Preferred

  Master’s degree or PhD in Computer Science or related technical field.

Minimum Professional
Experience

• 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML
  infrastructure, Natural Language Processing or Computer Vision.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience
  with an advanced degree in an industry setting.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence,
  deep learning, or natural language processing.
• Excellent problem-solving and troubleshooting skills to address complex technical challenges.
• Effective communication and collaboration skills to work with cross functional teams.

Preferred Professional
Experience

• 2 years of experience with improving performance during large scale data processing
• Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with
  Human Feedback (RLHF).
• Excellent data analysis skills.