About

Vishnu Anilkumar is a highly experienced Lead Machine Learning Engineer at Pixis with a passion for developing and deploying machine learning algorithms and entire training and inference pipelines. With almost 5 years of relevant experience, Vishnu is well-versed in the latest technologies and techniques used in the field of AI. Vishnu is particularly interested in the development of real-world applications using AI, and has worked with exceptional and challenging clients to deliver high-quality solutions. He has experience in predictive analysis, data governance, and the design and analysis of controlled randomized tests. In his previous role as a Senior Machine Learning Engineer at Quantiphi, Vishnu played a key role in delivering the CLTV model with North Star Metric as monthly revenue for Dawn Foods. He also worked on next purchase forecasting for Henry Schein, and proposed the Next Best Product and CLTV model for Bank of Montreal during the pre-proposal phase. Vishnu managed and mentored a team of seven MLEs in multiple projects, providing guidance to the R&D and product teams in the marketing analytics domain. Before joining Pixis, Vishnu worked as a Consultant Machine Learning Engineer at Cleareye.ai. In this role, he used machine learning and statistical modeling techniques to develop and evaluate algorithms to improve performance, quality, data management, and accuracy. Vishnu actively engaged other teams across the company to identify security scenarios where machine learning/applied statistics can be used, and lead the development of solutions to these problems. Vishnu holds a Master's Degree in Computer Science - Machine Intelligence from IIIT, and a graduation degree in Applied Physics from KKTm Govt. College, Pullut. He has also completed Vocational Higher Secondary Education in Science from High School. Vishnu has an extensive tech stack, including ML, AI, NLP, Computer Vision, Django, Python, MongoDB, AWS, GCP, BERT, Random Forest, Big Data, Web, Docker, Data Scientist, Research Scientist, TensorFlow, SQL, Search, Flask, SVM, XGBoost, Keras, CNN, OpenCV, Deep Learning, Selenium, Scikit, Elastic Search, Pytorch, and Azure.