Machine Learning Engineer

About the Institute

Role overview

Key responsibilities

• Collaborate with research teams to understand technologies and adapt and integrate them into the codebase.
• Build systems for machine learning model lifecycle stages, including data preprocessing, pre-training, post-training, and evaluation, especially for foundation models.
• Participate in or lead design reviews and help select technologies.
• Review code for style, accuracy, testability, and efficiency.
• Contribute to documentation and educational content and update it based on product or program changes and user feedback.
• Triage, debug, track, and resolve issues, analyzing impacts on hardware, networks, services, and quality.
• Contribute to research papers and represent MBZUAI at conferences and industry events, showcasing HPC and deep learning capabilities.
• Perform other duties reasonably directed by the line manager in support of the role’s objectives.

Academic qualifications

• A bachelor’s degree or equivalent practical experience is required.
• A master’s degree or PhD in Computer Science or a related technical field is preferred.

Professional experience and skills

• At least 3 years of software engineering experience, including experience with ML models, ML infrastructure, NLP, or computer vision.
• At least 2 years of software development experience in one or more programming languages, or 1 year of such experience with an advanced degree in an industry setting.
• At least 2 years of experience with data structures or algorithms in an academic or industry setting.
• At least 2 years of experience with ML algorithms and tools, AI, deep learning, or NLP.
• Strong problem-solving, troubleshooting, communication, and collaboration skills are required.
• Experience improving performance in large-scale data processing, hands-on SFT or RLHF experience, and strong data analysis skills are preferred.