About

Yaman Singhal is a highly motivated and talented Junior Software Developer with a passion for machine learning and research. Currently employed at Grassdoor Logistics Technologies Pvt Ltd, Yaman has gained 2.19 years of relevant experience in software engineering, machine learning, and research. Yaman's expertise in machine learning and research is evident from his previous work experiences. As a Machine Learning Intern at Tutree, he gained hands-on experience in developing machine learning models and algorithms. He also worked as a Research Intern at Mitacs, where he conceptualized research on federated learning with a professor at the University of Calgary. His contributions in making various defense techniques from scratch and creating reports on various research papers related to federated learning demonstrate his research skills. At Grassdoor Logistics Technologies Pvt Ltd, Yaman has been working as a Junior Software Developer, where he has been involved in developing software solutions for logistics management. He has gained experience in software development and has honed his skills in software engineering. Yaman's technical skills include software engineering, machine learning, and research. He is proficient in programming languages like Python, Java, and C++. He is also skilled in machine learning frameworks like TensorFlow, Keras, and PyTorch. Yaman holds a Mitacs GRI'21 from the University of Calgary, where he gained knowledge and skills in research and innovation. He is a quick learner and has a strong work ethic. He is always eager to learn new things and is a team player. Overall, Yaman Singhal is a talented and driven Junior Software Developer with a passion for machine learning and research. His technical skills, relevant experience, and educational background make him a valuable asset to any organization he works with.