Resume

ML engineer with 3+ years designing intelligent AI systems, deploying models, and integrating cloud-native infrastructure. Experienced across ML research, data engineering, and backend development with a focus on LLM agents, semantic search, and real-time analytics.

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Work Experience

ML Research Engineer – Cloud Systems LLC

Jul 2024 – Present | Remote

Context: Modernize analytics for diverse cloud datasets.
Actions: Created optimized SQL queries and streaming pipelines, automating ETL across sources with Airflow.
Impact: Delivered reliable data feeds and reduced manual prep by 40%.

ML Research Engineer – Virginia Tech

Sep 2024 – Jul 2024 | Blacksburg, VA

Context: Classify genomic sequences using DNA foundation models.
Actions: Fine-tuned DNABERT and HyenaDNA with LoRA and soft prompting; automated preprocessing for 1M+ sequences using Biopython and Airflow.
Impact: Reached 94%+ accuracy and cut iteration cycles by 40%.

Research Assistant – Virginia Tech

Jun 2023 – May 2024 | Blacksburg, VA

Context: Support genomic research with scalable data workflows.
Actions: Orchestrated ETL pipelines with Airflow and Glue, and automated model retraining via custom CI/CD scripts.
Impact: Improved data availability 50% while reducing manual effort 40%.

Data Engineer – UJR Technologies Pvt Ltd

Jul 2021 – Dec 2022 | Hyderabad, India

Context: Transition legacy data platform to real-time analytics.
Actions: Migrated batch jobs to Kafka/Spark streaming and optimized Snowflake schemas with materialized views.
Impact: Cut processing latency 30%, sped deployments 25%, and maintained 99.9% uptime.

Skills

Programming: Python, R, SQL, JavaScript/TypeScript, Node.js
Frameworks: PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers, LangChain, LangGraph
AI Systems: LLM Fine-Tuning, RAG, Prompt Engineering, Agents, GANs
Cloud & Infra: AWS, GCP, Docker, Kubernetes, SageMaker, MLflow, CI/CD
Data Engineering: Spark, Kafka, dbt, Airflow, ETL pipelines, Data Warehousing
Tools: Pandas, NumPy, Weights & Biases, Git, Tableau, Linux

Education

M.S. in Computer Science, Virginia Tech (Jan 2023 – Dec 2024) – CGPA 3.95/4
Bachelor’s in Computer Science, Anna University (Jul 2018 – May 2022) – CGPA 8.24/10

Publications

L. Miao, K. V. Dhulipalla, S. Kundu et al., "Leveraging Machine Learning for Predicting Circadian Transcription in mRNAs and lncRNAs," IEEE BIBM 2024.
M. Haghani, K. V. Dhulipalla, S. Li, "Harnessing DNA Foundation Models for Cross-Species Transcription Factor Binding Sites Prediction in Plant Genomes," ML in Computational Biology 2025.

Certifications

Building RAG Agents with LLMs – Nvidia
Introduction to Deploying RAG Pipelines for Production at Scale
Delivering Data-Driven Decisions with AWS
End-to-End Real-World Data Engineering with Snowflake
Google Cloud Data Engineering Foundations
AICTE-EduSkills Certificate in AWS Cloud
Coursera Machine Learning (Data-Driven Insights, ML Algorithms)