~10B
QPS supported
Tier-0 distributed counter services used across Meta's server fleet.
Currently pursuing an MBA and a self-directed MLOps transition; open to conversations about SRE, production engineering, platform engineering, and AI infrastructure roles.
Production engineer building toward AI infrastructure and MLOps.
Production engineer with three years at Meta building and operating Tier-0 distributed systems, now pairing that operational foundation with an MBA and a self-directed MLOps transition aimed at reliability engineering, MLOps, and AI infrastructure roles.
~10B
QPS supported
~100K
Servers
10+ PB
Indexed daily
Reliability surface
Production signal map
QPS supported
Tier-0 distributed counter services used across Meta's server fleet.
~10B
Indexed daily
Data indexed daily across Meta's distributed storage and indexing systems.
10+ PB
Faster turnup
Automation improvements for region and cluster turnup workflows.
10x
Power savings
Autoscaling improvements cut wasted compute capacity, saving an estimated 0.8 MW/hr across the fleet.
0.8 MW/hr
About
From Meta-scale production systems to MLOps.
I spent nearly three years as a Production Engineer inside Meta's Core Infra org, on the Core Data team, keeping Tier-0 services healthy at roughly 10 billion queries per second and 10+ petabytes indexed daily. That foundation was built earlier at Infosys, shipping and maintaining an internet banking platform, and through a Master's in Computer Science at UT Arlington focused on databases and intelligent systems.
I'm currently pursuing an MBA at Westcliff University (started January 2026) alongside a self-directed MLOps transition through InterviewKickstart, pairing Meta's production-systems discipline with machine learning infrastructure and the business judgment to make platform investment decisions. I'm building toward roles at the intersection of reliability engineering, MLOps, and AI infrastructure.
Quantified impact
Infrastructure scale, made observable and faster.
Measured results from operating Tier-0 infrastructure at Meta scale.
~100K
Servers
Servers across the Tier-0 distribution and indexing systems this role supported.
10+ PB
Indexed daily
Data indexed daily across Meta's distributed storage and indexing systems.
10x
Faster turnup
Automation improvements for region and cluster turnup workflows.
3-10m
Distribution time
Reduced remote storage distribution from 45-80 minutes to 3-10 minutes by moving from a push-based to a pull-based model.
0.8 MW/hr
Power savings
Autoscaling improvements cut wasted compute capacity, saving an estimated 0.8 MW/hr across the fleet.
Owned uptime and latency for Tier-0 services where an outage or a slow response propagates directly into product-facing failures.
Replaced manual, error-prone operational workflows with automation, autoscaling, and proactive monitoring, cutting toil and incident response time.
Raised developer velocity by building staging environments, internal tooling, and testing frameworks that other engineers relied on daily.
Experience
From internet banking systems to Meta Core Infra.
The through-line is production ownership: define the system, improve the workflow, reduce failure modes, and keep the service healthy.
July 2022 - April 2025
Production Engineer
Meta Platforms, Inc.
Menlo Park, CA
Core Infra/Core Data production engineering across Tier-0 counter, distribution, and indexing services serving low-latency, high-frequency workloads.
- Managed reliability, scalability, and performance for systems supporting ~10B QPS and indexing 10+ PB of data daily.
- Built automation for region and cluster turnup, making turnup workflows 10x faster.
- Moved remote data storage distribution from a push-based model to a pull-based model, reducing distribution time from 45-80 minutes to 3-10 minutes.
- Built monitoring and intelligent alerting for storage issues, usage spikes, and high-demand events such as New Year's traffic surges.
- Handled incident triage, resolution, RCA, capacity planning, forecasting, and autoscaling to maintain SLOs.
PythonC/C++ShellHiveSparkMemcachedCacheLibMercurialDockerKubernetesRocksDB
January 2022 - May 2022
Software Engineering Intern
Copart Inc.
Dallas, TX
Modified and extended Java-based applications while collaborating with program managers, business analysts, and technical leads.
- Worked across requirements analysis, application development, and existing-system improvements.
- Built and modified features across messaging, persistence, and integration layers using RabbitMQ, Kafka, Hibernate, MongoDB and MySQL.
JavaSpring CloudRabbitMQHibernateKafkaMachine LearningMySQLMongoDB
April 2021 - February 2022
Student Assistant, Web Developer
The University of Texas at Arlington
Arlington, TX
Supported web development for the Office of the Provost and Academic Affairs while completing graduate study.
- Delivered web development tasks in an academic environment with multiple stakeholders.
- Balanced production web work with graduate coursework in AI, databases, and intelligent systems.
Web DevelopmentAccessibilityContent UpdatesStakeholder Collaboration
September 2017 - August 2020
Senior System Engineer / System Engineer
Infosys Ltd.
Bengaluru, India
Full-stack engineering for an internet banking platform in a distributed Agile environment with direct client exposure.
- Gathered requirements and implemented feature modules for core banking workflows, working directly with client stakeholders on design proposals.
- Led migration of a legacy module to a modernized architecture with minimal disruption to live banking operations.
- Raised team engineering velocity through internal tooling, unit and automation testing, and CI/CD adoption.
ReactJavaScriptjQueryJ2EESpring BootIBM WebSphereTomcatMSSQLGit
GitHub and research
Selected work that supports the infrastructure story.
Public repositories and research projects across reliability, computer vision, and data analysis.
A curated guide for SRE interview preparation, capturing reliability concepts, systems thinking, and production-readiness patterns.
SREDistributed SystemsInterview Prep
Computer vision pipeline for detecting dogs and cats in CAD-model-derived images, covering data preprocessing, model training, and evaluation.
Jupyter NotebookComputer VisionDeep Learning
Featured project
Exploring Image Super-Resolution Methods
CNN and GAN-based super-resolution research
Research project analyzing CNN and GAN-based techniques for image super-resolution, with parameter optimization to improve output quality.
AIComputer VisionCNNGAN
October 2020 - November 2020
Texas Weather Data Analysis
Clustering analysis on state weather patterns
Cluster analysis on five years of unstructured Texas weather data (2006-2010) to group stations by shared weather behavior.
Data AnalysisClusteringWeather Data
Data analysis project identifying which customer and campaign attributes correlated with marketing outcomes in a bank marketing dataset.
Data AnalysisMachine LearningResearch
Public coursework repository from a CodePath cybersecurity course, covering applied exercises in security fundamentals.
CybersecurityCourseworkSecurity Fundamentals
Skills
Operating range across reliability, systems, and delivery.
Grouped by where the work happened: reliability, infrastructure, ML foundations, and delivery.
Reliability & operations
SLO ownershipIncident responseRCAMonitoringAlertingCapacity planningAutoscaling
Infrastructure & data systems
Distributed systemsStorage optimizationHiveSparkKafkaMemcachedCacheLibDockerKubernetesTerraform
AI/ML & MLOps foundations
MLOpsDeep LearningBig data & data science fundamentalsComputer VisionModel deployment
Programming
PythonC/C++JavaShell scriptingJavaScriptReact
Databases & tooling
MySQLMSSQLMongoDBRocksDBJenkinsGitMercurialPostmanJUnit
Leadership signals
High-level designClient communicationCross-functional collaborationDeveloper productivityTesting frameworks
Certifications
Continuous learning map.
Learning Terraform
LinkedIn · Aug 2025
Terraform
Deep Learning
The University of Texas at Arlington · May 2022
AI / Computer Vision
Big Data Management and Data Science
The University of Texas at Arlington · May 2022
Data Science / Big Data
Apache Kafka Essential Training: Getting Started
LinkedIn · Jan 2022
Kafka
Python (Basic)
HackerRank · Sep 2021
Python
Machine Learning Course in Python and R
Udemy Academy · Jun 2018
Machine Learning / Python / R
Linux Training
IIT Bombay · Feb 2014
Linux
Education
AI, databases, intelligent systems, and computer engineering.
Westcliff University
Master of Business Administration
Jan 2026 - Present
MBA coursework paired with a self-directed MLOps transition, building toward AI/ML infrastructure roles.
The University of Texas at Arlington
Master of Science, Artificial Intelligence / Computer Science
Aug 2020 - May 2022
Specialization in Database and Intelligent Systems; GPA 3.7/4.0.
Dharmsinh Desai University
Bachelor of Technology, Computer Engineering
2013 - 2017
Coursework spanning software systems, programming, and applied computer engineering.