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Professional Summary
Senior Machine Learning & Data Engineer with 10+ years building
production-scale AI/ML systems and data platforms serving 100M+ users.
Expertise in designing end-to-end ML infrastructure, deploying LLM-based
applications, and architecting distributed data systems processing 100T+
records daily. Proven track record delivering measurable business impact
through ML-driven solutions at Fortune 100 companies. Deep experience with
cloud-native architectures, MLOps, and real-time streaming systems.
Technical Expertise
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Machine Learning/AI: Deep Learning (TensorFlow, PyTorch),
LLMs & Generative AI (LangChain, LangGraph, RAG, Prompt Engineering),
NLP, Computer Vision, ML Model Optimization, A/B Testing, Feature
Engineering
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MLOps & Infrastructure: Kubernetes, Docker, Kubeflow,
MLflow, Airflow, Model Serving (TensorFlow Serving, TorchServe), CI/CD for
ML, Model Monitoring & Observability
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Big Data & Cloud: GCP (BigQuery, Dataflow, Vertex AI,
Cloud Storage), AWS (SageMaker, EMR, S3, Lambda), Apache Spark, Hadoop,
Kafka, Flink
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Programming & Frameworks: Python (NumPy, Pandas,
Scikit-learn, PySpark), Java, Rust, SQL, Scala
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Data Engineering: Real-time Streaming, ETL/ELT Pipelines,
Data Lakes, Data Warehousing (Snowflake, Redshift), OLAP/OLTP, Data Quality
Frameworks
Professional Experience
Senior Data Engineer, Cisco; Raleigh, NC —
2021-Present
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Contributed to ML infrastructure development for network
intelligence platform serving Fortune 100 telecom provider (120M+
customers), enabling predictive network analytics and anomaly detection at
scale
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Architected and deployed production LLM-powered application
using LangChain and RAG, reducing network troubleshooting time by 60% and
improving customer satisfaction scores by 25%
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Built near real-time anomaly detection system analyzing
10,000+ network devices using parallel processing, preventing $10M+ in
potential network outages
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Designed fault-tolerant data pipeline with 99.99% uptime
protecting $10B+ network infrastructure through real-time threat detection
Senior Data Engineer, 84.51°; Cincinnati,
OH — 2020-2021
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Architected enterprise-scale ML feature store processing
20B rows (5TB+) with 40+ transformation steps, reducing feature engineering
time by 80% for data science teams
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Led performance optimization initiative achieving 40%
latency improvement through distributed computing optimization (Spark
tuning, data partitioning strategies) for customer analytics pipelines
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Implemented real-time recommendation system data pipeline
supporting personalized marketing campaigns, contributing to $50M+
incremental revenue
Data / Machine Learning Engineer, Cisco;
Bengaluru, India — 2019-2020
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Designed multi-cloud data synchronization platform enabling
real-time data replication between GCP and Snowflake with zero data loss,
supporting ML model training workflows
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Implemented incremental ETL pipelines using Airflow and
Dataflow, reducing data processing costs by 35% through intelligent
incremental loading strategies
Software Engineer, Global Data;
Hyderabad, India — 2018
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Engineered scalable web scraping platform using distributed
architecture (Scrapy, Celery, Redis), processing 1K+ pages daily from
diverse sources for ML training data
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Optimized data extraction pipeline implementing intelligent
proxy rotation and multi-processing, achieving 3x throughput improvement and
99.9% reliability
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Led team of 5 engineers developing 12 full-stack
applications for US federal clients using microservices architecture,
delivering projects on-time with 98% quality metrics
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Designed real-time analytics dashboards using Tableau and
SSRS, processing 10M+ daily records and enabling data-driven decision making
for stakeholders
Project / Systems Engineer,
Royal Oman Police;
Muscat, OM — 2013-2015
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Architected high-performance OLTP/OLAP database system for
nationwide speed camera network, handling 500K+ daily transactions with
sub-100ms query latency
Automation Engineer,
Mott MacDonald; Abu Dhabi, UAE —
2009-2012
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Automated industrial control systems for water treatment
facilities using PLC and SCADA, improving operational efficiency by 40%
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Led installation of automated monitoring systems at major
infrastructure projects (Yas Island development, housing communities)
Education
B. Tech in Computer Science Engineering — Andhra University,
2009
Additional Achievements
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Scale: Built ML/data systems processing 100T+ transactions
daily in near real-time.
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Impact: Delivered solutions contributing to $20M+
measurable business value