SUMMARY Highly motivated Software Engineer specializing in AI/ML systems and data infrastructure, with a Master's degree (expected May 2025). Proven experience coding in Python, C++and SQL, adept at designing and deploying solutions leveraging LLMs, RAG and Embeddings within Kubernetes/Cloud environments. Eager to contribute to Microsoft's live service operations by focusing on code quality, deployment best practices and ensuring system reliability at scale.

Varaprasad Bathula

SUMMARY Highly motivated Software Engineer specializing in AI/ML systems and data infrastructure, with a Master's degree (expected May 2025). Proven experience coding in Python, C++and SQL, adept at designing and deploying solutions leveraging LLMs, RAG and Embeddings within Kubernetes/Cloud environments. Eager to contribute to Microsoft's live service operations by focusing on code quality, deployment best practices and ensuring system reliability at scale.

Available to hire

SUMMARY Highly motivated Software Engineer specializing in AI/ML systems and data infrastructure, with a Master’s degree (expected May 2025). Proven experience coding in Python, C++and SQL, adept at designing and deploying solutions leveraging LLMs, RAG and Embeddings within Kubernetes/Cloud environments. Eager to contribute to Microsoft’s live service operations by focusing on code quality, deployment best practices and ensuring system reliability at scale.

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Experience Level

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

AI/ML Engineer at Uber / R K Software Services LLC
June 1, 2025 - Present
Fine-tuned large language models with Hugging Face, improving prediction accuracy by 30% and reducing task completion time by 40%, enabling enterprise clients to scale production NLP workloads. Deployed CNN and Transformer-based computer vision models on AWS SageMaker using Docker and FastAPI, achieving 98% classification accuracy and reducing inference latency by 25% across real-time image recognition systems. Automated CI/CD pipelines with GitHub Actions, Docker, and Kubernetes for ML workflows, improving deployment reliability by 30% and reducing release cycle times by 35%. Designed real-time monitoring and alerting frameworks for ML models, reducing production failures by 20% and ensuring reliable performance in mission-critical client-facing applications. Integrated bias detection algorithms and fairness metrics, reducing model bias by 20% and improving AI ethics compliance. Implemented privacy-preserving AI techniques and encryption strategies, strengthening data security and ach
AI/ML Engineer at Intello Labs
April 1, 2020 - March 1, 2023
Designed predictive models using regression, clustering, and decision trees in scikit-learn, increasing forecasting accuracy by 35% and enabling clients to optimize retail inventory and financial demand planning decisions. Built RNN and Transformer architectures in PyTorch for time-series forecasting, reducing forecasting errors by 22% and delivering highly accurate demand predictions for global retail and supply chain clients. Engineered ETL pipelines with SQL, Pandas, and NumPy, reducing data preparation time by 45%, improving dataset quality, and accelerating downstream model training workflows across multiple business units. Standardized feature engineering processes, improving data consistency and boosting model performance by 18%. Delivered Tableau and Power BI dashboards integrating predictive outputs, reducing reporting cycles by 30% and enabling executives to make data-driven decisions faster. Automated experimentation workflows with Azure ML and Google Colab, cutting experime

Education

Master of Science in Data Science at University of Memphis
January 11, 2030 - May 1, 2025

Qualifications

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Industry Experience

Software & Internet, Professional Services, Healthcare, Financial Services, Retail