Professional Summary
Machine Learning Engineer with 5 years of experience in designing and deploying ML solutions across finance, healthcare, and consumer goods domains. Specialized in end-to-end ML lifecycle: data ingestion, cleaning, preprocessing, feature engineering, model training, evaluation, and deployment. Proficient in Python, SQL, and Spark, with hands-on experience in building scalable data pipelines and ML workflows. Extensive experience with AWS services and familiar with Azure cloud tools. Skilled in machine learning, deep learning frameworks, NLP techniques, and Big Data tools. Adept at data visualization and translating complex insights into actionable business outcomes. Experienced in MLOps and CI/CD pipelines.
Skills
Programming
Python (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, Boto3) SQL Scala Bash C++
Machine Learning
Classification Regression Time Series Forecasting Clustering XGBoost Random Forest SVM Neural Networks
NLP
spaCy NLTK BERT LDA Word2Vec Named Entity Recognition Text Summarization
Cloud Platforms
AWS: S3 EC2 Lambda SageMaker Glue Athena Redshift CloudFormation
Azure: Data Factory Cosmos DB Azure DevOps Azure Databricks
Big Data Ecosystem
Spark (PySpark, SparkSQL) Hadoop Hive Kafka
MLOps & DevOps
MLflow Airflow Jenkins Git Docker Kubernetes Terraform Ansible
Databases
MySQL PostgreSQL MongoDB Cassandra DynamoDB
Visualization Tools
Tableau Power BI Matplotlib Seaborn Plotly
Frameworks & APIs
FastAPI Flask Django REST Framework OpenCV
Version Control & Others
Git GitHub Agile Scrum Jira Postman PyTest Prometheus Grafana
Projects
Medical Image Segmentation – Deep Learning (Polyp Detection)
Tech Stack: Python, PyTorch, OpenCV, NumPy, Albumentations, Scikit-learn
- Developed a U-Net++ model for polyp segmentation from colonoscopy images (CVC-ClinicDB dataset).
- Implemented preprocessing and data augmentation (Albumentations).
- Utilized OpenCV and PyTorch; trained on GPU.
- Evaluated with IoU and Dice Coefficient, achieving high accuracy.
- Aids early detection in clinical settings.
AI Video Summarization Project using Mixtral, Whisper, and AWS
Tech Stack: Python, FFmpeg, Whisper, Mixtral, Flask, AWS EC2
- Developed an AI tool for extracting key concepts from educational videos (Whisper for transcription, Mixtral for summarization/quiz).
- Automated audio extraction (FFmpeg); deployed on GPU-enabled AWS EC2.
- Built a web interface (Flask) with feedback capture.
Financial Reporting Agent with Microsoft Fabric & RAG
Tech Stack: Python, Microsoft Fabric, OneLake, Azure, Vanna AI, GPT-4, LangChain
- Built a financial reporting agent using Microsoft Fabric (OneLake, lakehouse architecture).
- Developed a RAG system (GPT-4, LangChain) for contextual financial queries.
- Integrated Vanna AI for natural language-to-SQL.
- Automated data ingestion (Dataflow Gen2); visualized insights on a dashboard.
- Enabled scalable, low-latency analysis on Azure.
Education
Masters in Computer Science
Auburn University at Montgomery (AUM)
B. Tech
Andhra University
Certifications
AWS Certified Machine Learning Engineer
Azure Data Engineer Associate
Docker Certified Associate
Get In Touch
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your visions.
linkedin.com/in/gouthamcnakka (Update with actual LinkedIn)
github.com/gouthamcnakka (Update with actual GitHub)