Mihir Inamdar

Data Scientist

Bengaluru, Karnataka, India1 yr 8 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Improved OCR accuracy by 20% on low-resolution images.
Achieved F1-Scores of 99.8% for ticket classification.
Fine-tuned Llama-2 model for a Virtual Assistant Bot.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in AI-driven solutions across diverse industries.

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Skills

Core Skills

Machine LearningData ScienceOptical Character Recognition (ocr)Computer VisionNatural Language Processing (nlp)Predictive ModelingGenerative Ai

Other Skills

Artificial Intelligence (AI)Generative Neural NetworksFine TuningMLOpsResearch SkillsPredictive AnalyticsImage ProcessingNeural Machine Translation (NMT)Recommender SystemsContainerizationPyTorchHealthcareCross-functional Team LeadershipCommunity EngagementGoogle Cloud Platform (GCP)

About

As a Machine Learning Engineer at Quoppo, I apply my skills in machine learning, deep learning, and applied machine learning to develop innovative solutions for various industries. I have a strong background in information technology, having completed my Bachelor of Engineering from Pune Institute of Computer Technology. I am passionate about leveraging cutting-edge technologies to solve real-world problems and improve user experiences. In my previous roles, I have demonstrated my ability to implement advanced neural network algorithms, collaborate with leading tech companies, and conduct comparative analyses to enhance prediction accuracy. For instance, I worked as an Undergraduate Research Fellow at Centre for Visual Information Technology (CVIT), where I improved OCR accuracy by 20% on low-resolution images and collaborated with Meta Reality Labs for experimental validations. I also developed and implemented a cutting-edge ML-based Ticket Qualification Platform as an NLP Intern at Textify AI, achieving impressive F1-Scores for predicting ticket categories and severity levels. I hold certifications in DLI C-FX-01 issued by NVIDIA, Private Equity and Venture Capital issued by Università Bocconi, and Tweet Emotion Recognition with TensorFlow issued by Coursera.

Experience

1 yr 8 mos

Total Experience

5 mos

Average Tenure

8 mos

Current Experience

Sutherland

Data Scientist

Aug 2025 – Present · 8 mos · Chennai, Tamil Nadu, India · On-site

Topmate.io

AI/ML Mentor

May 2025 – Aug 2025 · 3 mos · India · Remote

Mentoring AI Practitioners and ML Engineers.
Page: https://topmate.io/mihirinamdar

Quoppo

Machine Learning Engineer

Oct 2024 – Apr 2025 · 6 mos · Pune, Maharashtra, India · Hybrid

Artificial Intelligence (AI)Data ScienceGenerative Neural NetworksFine TuningMachine LearningMLOps

Centre for visual information technology (cvit)

Undergraduate Research Fellow

Mar 2024 – Aug 2024 · 5 mos · Hyderabad, Telangana, India · On-site

Implemented advanced neural network algorithms to enhance OCR accuracy by 20% on low-resolution images.
Collaborated with Meta Reality Labs for experimental validations, achieving a breakthrough in image processing technology.
Conducted a comparative analysis between diffusion models and GANs to improve prediction accuracy by 15%.

Research SkillsOptical Character Recognition (OCR)Predictive AnalyticsImage ProcessingComputer VisionNeural Machine Translation (NMT)+1

Textify ai (backed by angellist)

NLP Intern

Oct 2023 – Jan 2024 · 3 mos · Indore, Madhya Pradesh, India · Remote

Developed and implemented a cutting-edge ML-based Ticket Qualification Platform using FastAPI, Langchain, Node.js, and MongoDB.
Achieved an impressive F1-Score of 99.8% for predicting ticket categories and 93.7% for severity levels with the NLP model developed.
Enhanced user experience by integrating FastAPI framework and Langchain algorithm to reduce translation errors and improve server response time.

Recommender SystemsPredictive ModelingPredictive AnalyticsContainerizationNeural Machine Translation (NMT)Fine Tuning+1

Cellstrat

Generative AI Intern

Jun 2023 – Sep 2023 · 3 mos · Bengaluru, Karnataka, India · Hybrid

Fine-tuned the Llama-2 model on the Legal Documents dataset to create a Virtual Assistant Bot achieving 85% accuracy.
Collaborated with the team to reduce conversational AI model's error rate by 10%.
Organized experiments to enhance LLM technology effectiveness.

Data SciencePyTorchPredictive ModelingOptical Character Recognition (OCR)ContainerizationNeural Machine Translation (NMT)+2

Fellowship.ai

Data Science Fellow

Jan 2023 – Apr 2023 · 3 mos · San Francisco, California, United States · Remote

Led a finance-based project to design and fine-tune a Language Model (LLM) for expert financial advice using deep learning and NLP techniques.
Trained the model on curated financial data, achieving a 8% improvement in accuracy.
Developed Python code to generate Q&A pairs from over 30 websites using OpenAI and Beautiful Soup, achieving a total of 2,000 Q&A pairs.

Data ScienceRecommender SystemsPyTorchNeural Machine Translation (NMT)Fine TuningNatural Language Processing (NLP)