ayushkhaire
About me
– Partial blindness
– Low vision
– Hearing loss
Work Experience
AIML intern
Impacto Digifin Technologies
2025-08-10
-
2025-11-16
Aug - Nov 2025
Exploring finance , LLMs , OCR and voice agents
Developed and executed evaluation pipelines for LLMs, focusing on document understanding, accuracy benchmarking, and reliability analysis. Built end-to-end vision–text recognition pipelines, including preprocessing, OCR/ML models, and result validation for high-accuracy extraction. Designed and implemented real-voice generation agents using speech synthesis, enhancing naturalness and conversational quality in voice interfaces. Focus on efficient local models
Machine Learning Engineer
Freelance
2026-04-29
-
Present
Working remotely with a Japanese client in biological machine Learning.
Education
Computer Science and Engineering
Bachelor's in technology
2022-09-15
-
2026-07-01
IIIT nagpur
B Tech in Computer science ( Specialization in data science )
nov 2022 - jul 2026
Score: 7.5 / 10
Developed a deep expertise in computer science with specialization in data science and analytics
Pursued a Bachelor of Technology in Computer Science and Engineering with specialization in Data Science and Analytics at the Indian Institute of Information Technology, Nagpur. Throughout the program, developed a strong interdisciplinary foundation across computer science, mathematics, machine learning, and applied data analytics, with a practical and research-oriented learning approach. Built core mathematical understanding through subjects such as Calculus for Data Science, Linear Algebra, Probability and Statistics, Advanced Probability, Discrete Mathematics, and Graph Theory. These subjects were studied not only from a theoretical perspective but also in relation to their applications in machine learning, optimization, statistical modeling, and algorithmic reasoning. Developed programming and software engineering skills through coursework in Computer Programming, Object-Oriented Programming, Data Structures, Design and Analysis of Algorithms, Operating Systems, Database Management Systems, Computer Networks, and Foundations of Computing. Explored problem solving, computational efficiency, memory management, networking concepts, and backend system fundamentals while implementing practical programming assignments and analytical workflows. Focused extensively on the data science and artificial intelligence ecosystem through subjects such as Machine Learning, Artificial Intelligence, Data Mining and Warehousing, Big Data Analytics, Business Intelligence, Computer Vision and Deep Learning, Natural Language Understanding and Generation, Web Analytics, Sensor Data Analytics, and Generative AI. Studied classical machine learning algorithms, ensemble methods, statistical learning techniques, deep learning architectures, feature engineering, data preprocessing, visualization, model evaluation, and large-scale data analysis pipelines. Worked with modern data science tooling and practical analytical workflows through multiple “Tools and Practices for Data Science” courses, involving experimentation, data handling, visualization, model building, and analytical reporting. Developed familiarity with real-world datasets, structured and unstructured data processing, and iterative experimentation methodologies commonly used in industry and research environments. Explored specialized topics including data privacy and security, design thinking, entrepreneurship, technical communication, and technology innovation, helping build an understanding of the broader technological and societal aspects of computing systems and AI-driven applications. Completed academic projects focused on applied machine learning and analytics, involving problem formulation, experimentation, implementation, and evaluation. Gained exposure to end-to-end project workflows including data collection, preprocessing, model development, validation, visualization, and presentation of findings. Alongside formal coursework, actively pursued self-driven learning in machine learning engineering, competitive data science, and practical AI systems by experimenting with analytical pipelines, feature engineering strategies, streaming and time-series style modeling approaches, web technologies, and accessibility-focused software ideas. Developed a habit of learning through implementation, experimentation, debugging, and iterative refinement of systems rather than relying solely on theoretical study.
Disability-Info
UDID
Yes
UDID Number
MH2050120050049670
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Disability Percentage (As per certificate)
87