Aviral Sharma
About Aviral Sharma
Aviral Sharma is an AI Engineer at HTC Global Services with a background in machine learning and artificial intelligence, holding degrees in Aerospace Engineering from IIT Kanpur and UPES.
Title: AI Engineer at HTC NXT
Aviral Sharma holds the title of AI Engineer at HTC Global Services, working specifically within the HTC NXT division. His role started in 2023 and is based in Bengaluru, Karnataka, India. In this capacity, he is involved in various advanced AI projects that contribute to the innovative landscape of HTC NXT.
Previous Experience: Machine Learning Engineer at Paninian
Prior to his current position, Aviral Sharma worked at Paninian as a Machine Learning Engineer. His tenure lasted from 2022 to 2023, during which he was based in Bengaluru, Karnataka, India. In this role, he engaged in several machine learning initiatives that advanced the company's technological endeavors.
Previous Experience: Roles at AIRODYN SYSTEMS PVT LTD
Aviral Sharma has a diverse background with AIRODYN SYSTEMS PVT LTD, holding multiple roles in 2020 and 2021. He served as an Artificial Intelligence Engineer for 5 months in Delhi, India, and earlier as a Human Resources and Business Development Manager for 2 months. These roles helped him acquire a multi-faceted skill set that spans both technical and managerial domains.
Education and Expertise: IIT Kanpur and UPES
Aviral Sharma has a strong academic background in aerospace engineering. He obtained his Master of Science (MS) in Aerospace Engineering from the Indian Institute of Technology, Kanpur, from 2018 to 2021. Earlier, he completed his Bachelor of Technology (B.Tech) in Aerospace Engineering with a specialisation in Avionics from UPES, graduating in 2017.
Key Projects and Implementations
Throughout his career, Aviral Sharma has led and contributed to multiple high-impact projects. He implemented a Natural Language based Model Explanations feature that increased user trust and confidence in AI-driven decisions by 25%. He developed a GPT-3.5-turbo powered chatbot for house insurance claims processing, which reduced claims processing time by 30%. Additionally, he led the design and development of a comprehensive MLOps library and implemented the Automatic Generation of APIs for inference, thereby reducing deployment errors and expediting AI solution delivery by 20%. Furthermore, he leveraged unsupervised machine learning to analyze a diabetes dataset, optimizing patient treatment strategies.