Manasa Varala
Open to work5 years experienceSenior Machine Learning Engineer
Senior Machine Learning Engineer with 5 years of experience shipping robust ML systems to production.
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Work Experience
Senior Machine Learning Engineer
Lenovo
- Implemented ML systems to production by designing and deploying scalable feature pipelines for large-scale structured data, resulting in a 15% reduction in data processing latency for critical analytics dashboards.
- Developed robust data ingestion processes for diverse real-world exports, establishing a resilient schema design that accommodated schema drift across 5+ data sources, enhancing data quality and reliability.
- Orchestrated end-to-end machine learning workflows using Python and SQL, from data preparation to model serving and monitoring, supporting multiple internal applications with high-availability predictions.
- Engineered gradient-boosted tabular systems for predictive analytics, achieving a 10% improvement in model accuracy for key business metrics by meticulously handling label definition and preventing data leakage.
- Built comprehensive experiment tracking and monitoring tools for ML models, enabling continuous iteration and ensuring model performance stability in production over 20+ deployment cycles.
Machine Learning Engineer
Tech Mahindra
- Designed and optimized data ingestion pipelines using Python and Spark for processing high-volume structured data from various real-world exports, improving data availability by 25% for downstream ML applications.
- Developed and maintained core data schemas for critical datasets, ensuring data integrity and consistency across multiple projects and effectively managing schema drift over a 3-year period.
- Constructed feature pipelines for machine learning models, transforming raw data into production-ready features, which supported the development of 3 distinct predictive models.
- Applied strong applied ML on tabular data to develop predictive models, utilizing techniques like gradient boosting, which led to actionable insights for client projects.
- Automated data quality checks and validation processes within data pipelines, reducing manual data error detection time by 30% and ensuring reliable inputs for ML systems.
Projects
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Leaderboard Standings
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Assessment Highlights
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AI Collaboration Score
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Role Compatibility Profile
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Achievements
AWS Certified Cloud Practitioner
AWS Certified Cloud Practitioner
Microsoft Azure AI Fundamentals (AI-900)
Microsoft Azure AI Fundamentals (AI-900)
Machine Learning with Python
Machine Learning with Python
About Details
Professional Bio
Senior Machine Learning Engineer with 5 years of experience shipping robust ML systems to production. Expert in Python, SQL, dbt, and Spark, with extensive experience in data ingestion, schema design, feature pipelines, and orchestration for complex structured data.
Master of Science in Computer Engineering
University of North Texas ( - Present)