Akhila

Applied Data Science and Machine Learning Engineer

Bengaluru, India 3+ yrs exp 86 · Excellent

About

Machine Learning Engineer with hands-on experience in applied data science, building and evaluating machine learning models using Python. Exposure to NLP and computer vision use cases including text classification and image-based multi-class prediction. Skilled in data preprocessing, feature engineering, model training, and performance evaluation, with a focus on data-driven problem solving in engineering environments.

Skills & Expertise (14)

Python Advanced

8.0/10

Years Exp

Convolutional Neural Networks Intermediate

7.5/10

Years Exp

Deep Learning Intermediate

7.5/10

Years Exp

Image Classification Intermediate

7.5/10

Years Exp

Exploratory data analysis Intermediate

7.0/10

Years Exp

Sentiment Analysis Intermediate

7.0/10

Years Exp

Supervised Learning Intermediate

7.0/10

Years Exp

Model Evaluation Intermediate

7.0/10

Years Exp

Text Preprocessing Intermediate

7.0/10

Years Exp

Data Preprocessing Intermediate

7.0/10

Years Exp

Jupyter Notebook Intermediate

7.0/10

Years Exp

Feature Engineering Intermediate

7.0/10

Years Exp

Data Structuring Intermediate

7.0/10

Years Exp

Git Intermediate

6.5/10

Years Exp

Work Experience

AI/ML Developer

The School of Ancient Wisdom

May 2026 - Present

Developing and implementing AI/ML solutions for real-world agricultural and animal healthcare applications using Python and deep learning techniques. Worked on cattle mastitis detection, focusing on both udder and teat conditions, using computer vision and image-based machine learning approaches. Currently working on a cattle tick detection project, involving image dataset collection, annotation, preprocessing, model development, and evaluation. Built and integrated machine learning inference pipelines with FastAPI and Streamlit to develop interactive, deployment-oriented applications and demonstration interfaces. Developed Streamlit-based applications for model inference, visualization, and user interaction, with FastAPI used for backend API integration. Supported end-to-end ML workflows including data collection, preprocessing, model training, evaluation, debugging, and deployment-oriented testing. Contributed to the development of practical AI solutions by integrating trained models into user-friendly applications for real-world use cases.

Assistant Data Scientist

Institute of Health Management & Research

Dec 2024 - Jun 2026

Supported applied machine learning and data science workflows, including data structuring, preprocessing, feature engineering, and exploratory data analysis on structured and unstructured datasets. Built, trained, and evaluated machine learning and deep learning models using Python for classification and prediction use cases. Implemented NLP models for text classification and sentiment analysis, and CNN-based models for image classification. Provided technical support for ML pipelines, including data debugging, model validation, deployment-oriented demos, and documentation of workflows and results.