Headline

Machine Learning Engineer | Turning Data, APIs & ML Models into Real-World Products

About

I’m a Computer Science graduate (AI & ML) with a strong focus on building data-driven systems and applying machine learning to solve real-world problems. My core experience lies in working with SQL and Python to build data pipelines, clean and validate datasets, and ensure data accuracy across systems. I’ve designed ETL workflows, implemented data quality checks, and validated API-driven data to detect inconsistencies and ensure reliable downstream usage. Alongside data engineering and analytics, I’ve worked on machine learning and NLP projects, including sentiment analysis systems and model evaluation pipelines. This has given me exposure to the full lifecycle — from data preparation and feature handling to model evaluation and performance optimization. Key areas I’ve worked on: --Data preparation, cleansing, and transformation for analytics and ML --Building and monitoring ETL pipelines --Writing optimized SQL queries for reporting and analysis --Implementing data validation and data quality checks --Developing ML/NLP models and evaluating prediction accuracy --Creating dashboards and tools to communicate insights I’m particularly interested in roles at the intersection of Data Analytics, Machine Learning, and Data Assurance, where high-quality data and intelligent models drive business decisions. Currently seeking opportunities in Data Analytics, Data Science, and Machine Learning roles, where I can contribute to building reliable data systems and scalable ML solutions. Tech Stack: Python, SQL, Pandas, Scikit-learn, NLP, ETL Pipelines, REST APIs, GCP, Excel If you're working on data-driven or ML-focused problems, feel free to connect.

Location

Hyderabad

Work experience

Software Engineer at Ask jobs, Nov 2025 - Apr 2026 · 6 mos, Hyderabad, Automated master data extraction using Python (BeautifulSoup, Selenium), processing 10,000+ job records from 15+ sources; supported creation, updates, and deletion of structured datasets while reducing manual effort by 35%. Built data validation, cleansing, and normalization scripts handling JSON, CSV, and Excel formats; improved data integrity and consistency with a 99% pipeline success rate. Developed SQL-based analysis and reporting automation; supported reporting requirements by generating daily analytical datasets deployed on cloud infrastructure (GCP) for 5,000+ users.

Education

Bachelor of Technology, CSE(AIML), Keshav Memorial Institute of Technology-Hyderabad

Sri Chaitanya junior kalasala

Public links

github: https://github.com/4ryt