About

Ammar Alqatari is an experienced Machine Learning Engineer currently working at Abacus.AI. With a relevant experience of 3.78 years, he has gained extensive knowledge in the field of ML and AI. Ammar's past experience includes working as a Software Engineer at the Center for Spatial and Textual Analysis, where he honed his skills in the domain of software engineering. He has also worked as an Undergraduate Student Researcher at KAUST, where he collaborated with the Structural and Functional Bioinformatics Group to improve the efficiency of Nanopore-based DNA transcription algorithms. During his tenure, he developed a novel neural architecture that improved the inference speed of the best-performing open-source algorithm by more than 4x. Ammar has a Master's degree in Computer Science - Artificial Intelligence from Stanford University, which he completed in 2021. He also holds a Bachelor's degree in Computer Science with a Minor in Mathematics from the same institution, which he completed in 2019. Ammar's education has provided him with a strong foundation in the field of ML and AI. Ammar's tech stack includes ML, AI, Research Scientist, and Computer Vision. He has a keen interest in these domains and has been continuously working towards enhancing his skills. Ammar is a dedicated and hardworking individual who is always ready to take on new challenges. His passion for technology and innovation is evident from his work and achievements. Overall, Ammar Alqatari is a skilled Machine Learning Engineer with a strong educational background and relevant experience in the field. He is a valuable addition to any organization and has the potential to contribute significantly to the growth and success of the company.