About

Rishi Nair is a Deep Learning Engineer with over 7 years of relevant experience in the field. He is currently working as a Senior Machine Learning Engineer at Drip Capital, where he is responsible for developing and implementing machine learning models for various applications. Rishi has a strong background in supervised learning architectures and has recently been focusing on unsupervised learning, including autoregressive, flow, variational, and GAN models. He is also experienced in reinforcement learning and robotics, including SLAM, self-driving, and sensor fusion. Throughout his career, Rishi has worked with a range of technologies, including Python, C++, TensorFlow, PyTorch, Keras, and SQL. He has also worked extensively with NLP, computer vision, and object detection. Prior to his current role, Rishi worked as a Machine Learning Engineer at Smartek21, where he led a small team of data scientists focused on improving the backend NLP algorithms and associate analytics for the chatbot platform. He also worked on the core algorithms that power the Digital Meeting Assistant platform, including meeting summarization, NLP to SQL, and document analytics. Before that, Rishi worked as a Sr. Data Scientist at RisingMonks Technologies, where he developed a deep learning-based vision for a manufacturing client, creating a plant floor intelligence dashboard for safety, productivity, and efficiency. He also automated a manual parts counting process using Raspberry Pi board, achieving an accuracy of +-1%. Rishi holds a Bachelor of Engineering degree in Electrical, Electronics, and Communications Engineering from Savitribai Phule Pune University. He is skilled in various tech stacks, including AWS, GCP, Flask, MongoDB, Docker, and Kubernetes, and has experience in DevOps and microservices.