Machine Learning Engineer

Job description

About the Institute of Foundation Models We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. **As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development.**You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers. **The Role** 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. ### Professional Experience - Minimum - 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. ### Professional Experience - Preferred - 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.