Harjot Singh Parmar

Harjot Parmar is a seasoned machine learning engineer with extensive experience in building scalable distributed systems and ML infrastructure. With a Master’s in Systems Design Engineering from the University of Waterloo, he has a strong foundation in deep learning, data engineering, and system optimization. He has a proven track record of designing and optimizing complex distributed systems, such as low-latency data pipelines and cost-efficient cloud architectures. He also has patented multiple algorithms for vehicular accident detection and load estimation, leveraging geospatial and sensor fusion that leverage terabyte scale data. Harjot is skilled in a wide range of technologies, including Python, Kubernetes, TensorFlow, PyTorch, GCP, and AWS, and is passionate about using ML to solve real-world challenges.