I am a results-driven AI/ML Engineer and Data Scientist with 5+ years of experience extracting actionable business insights, building automated data pipelines, and optimizing advanced predictive models. I hold an MSc in Artificial Intelligence and have hands-on experience with deep learning, computer vision frameworks (YOLO, CNNs), and scalable cloud-based systems, delivering production-ready intelligent solutions.

Gnana Sushmitha

I am a results-driven AI/ML Engineer and Data Scientist with 5+ years of experience extracting actionable business insights, building automated data pipelines, and optimizing advanced predictive models. I hold an MSc in Artificial Intelligence and have hands-on experience with deep learning, computer vision frameworks (YOLO, CNNs), and scalable cloud-based systems, delivering production-ready intelligent solutions.

Available to hire

I am a results-driven AI/ML Engineer and Data Scientist with 5+ years of experience extracting actionable business insights, building automated data pipelines, and optimizing advanced predictive models. I hold an MSc in Artificial Intelligence and have hands-on experience with deep learning, computer vision frameworks (YOLO, CNNs), and scalable cloud-based systems, delivering production-ready intelligent solutions.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
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Work Experience

AI/ML Engineer at Accenture
December 1, 2025 - Present
ML Pipeline Management: Managed end-to-end ML pipelines from data cleaning through model monitoring, cutting processing times by 60% and enabling scalable pipeline infrastructure using Python automated scripts. Predictive Accuracy Tuning: Boosted model predictive accuracy to 88% on noisy real-world data tracking system execution steps via advanced hyperparameter optimization cycles with Scikit-learn. Cross-Functional Alignment: Worked closely with data teams to clean raw datasets and deploy stable, production-ready enterprise deep learning systems. Statistical Model Architecture: Designed advanced feature scaling, transformation rules, and structured variance criteria to govern ingestion layers prior to deployment stages. Anomaly Diagnostics Control: Integrated automatic fallback parameters and execution alerting setups to quickly detect prediction drift on live distributed servers. Performance Metric Verification: Audited computational metrics across pipeline execution models, deliver
Junior AI Engineer at Advanced Engineering Solutions
July 1, 2022 - July 1, 2025
Deep Learning Architecture: Developed a high-efficiency automated industrial classification system leveraging Mask R-CNN and AlexNet topologies to execute complex multi-scale feature extraction on raw image feeds. Spatial Pyramid Pooling: Integrated advanced Spatial Pyramid Pooling layers using OpenCV to preserve spatial data profiles and achieve high multi-class classification accuracy. Industrial Quality Assurance: Fully tested model consistency across varying factory illumination profiles, completely automating manual sorting and optimizing background object detection pipelines. Convolutional Layer Profiling: Evaluated model intermediate layer representations to enhance deep network performance and eliminate structural overfitting during localized validation steps. Image Preprocessing Frameworks: Built high-speed programmatic transformation routines for contrast adjusting, noise removal, and automated target image standardization. Hyperparameter Tuning Routines: Executed systematic
Python Fullstack Developer at Data Analytics & Predictive Systems Corp
January 1, 2020 - August 1, 2022
Regression Modeling Validation: Analyzed 17 years of automobile transaction details and macro-level fuel trends, contrasting linear, polynomial, and multivariate regression models utilizing Pandas dataframes. Cross-Validation Optimization: Executed strict cross-validation checks and mapped RMSE parameters to identify predictive degradation risks across distinct market car segments. Time-Series Feature Engineering: Engineered multi-layered time-series forecasting components to reveal high-impact dependencies driving long-term vehicle resale valuations. EDA Pipeline Engineering: Processed over 300,000 live pricing records to chart complex seasonal trends and pricing shifts using an automated Exploratory Data Analysis framework with Matplotlib. Interactive Dashboard Design: Built advanced analytics dashboard layers utilizing Matplotlib and Seaborn interfaces to instantly present strategic route window price metrics. Statistical Hypothesis Testing: Conducted comprehensive mathematical eval

Education

MSc Artificial Intelligence at Brunel University London
September 1, 2025 - September 1, 2026
BTech Computer Science & Engineering (AI & ML) at GITAM University
January 11, 2030 - July 7, 2026

Qualifications

Predictive Modelling, Model Fitting & Regression Analysis - Coursera
January 11, 2030 - July 7, 2026
Cluster Analysis, Association Mining & Model Evaluation - Coursera
January 11, 2030 - July 7, 2026
Regression Models - Coursera
January 11, 2030 - July 7, 2026
Data Structures and Algorithms - Coursera
January 11, 2030 - July 7, 2026
Project Management Fundamentals - IBM
January 11, 2030 - July 7, 2026

Industry Experience

Manufacturing, Software & Internet, Professional Services