Haris Ahmad

Haris Ahmad

Senior Machine Learning Engineer @ Bosch Global Software Technologies

About Haris Ahmad

Haris Ahmad is a Senior Machine Learning Engineer at Bosch Global Software Technologies, specializing in active learning pipelines and data ingestion for machine learning models. He has a background in software engineering and has worked on various projects, including improving recommendation systems and entity extraction in healthcare.

Work at Bosch Global Software Technologies

Haris Ahmad has been employed at Bosch Global Software Technologies as a Senior Machine Learning Engineer since 2023. He is based in Bengaluru, Karnataka, India. In this role, he focuses on developing advanced machine learning solutions and contributing to various projects that enhance the company's technological capabilities.

Education and Expertise

Haris Ahmad completed his Bachelor of Technology (BTech) in Computer Science at G.L. Bajaj Institute of Technology and Management from 2013 to 2017. He also attended The Aditya Birla Public School. His educational background has provided him with a strong foundation in machine learning and software engineering.

Background in Machine Learning Engineering

Prior to his current role, Haris worked as a Machine Learning Engineer at Quantiphi from 2021 to 2023, where he contributed to various machine learning projects. He also served as a Software Engineer at Capgemini from 2018 to 2021, gaining experience in software development and machine learning applications. His career began with an internship at Pianalytix in 2020.

Achievements in Machine Learning Projects

Haris Ahmad has implemented several significant machine learning projects. He developed active learning pipelines with VertexAI and Kubeflow for model retraining and validation during the COTA Healthcare Phase II project. He also created data ingestion pipelines from BigQuery for the Bumble recommendation engine, achieving a 20% improvement over the client's base model. Additionally, he achieved 90% extraction accuracy for healthcare-based entities from clinical notes.

Technical Contributions to GCP and Machine Learning

Haris developed a GCP Pipeline for Ecolab Inc., which achieved 70% average accuracy in extracting entities from order documents. This project led to notable improvements in system efficiency. His technical skills include proficiency in TensorFlow and Keras, which he utilized in delivering machine learning models for various applications.

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