Shrinkhla Sharma
Seattle,WA
Summary
Dedicated software engineer with over 9 years of experience specializing in distributed systems, large-scale data infrastructure, and machine learning. Proven track record at Amazon in architecting low-latency, high-throughput routing systems capable of handling over 1.8 million transactions per second and designing TB-scale data pipelines. Achievements include driving a 99% cost reduction through strategic architectural optimization. Committed to leveraging technical expertise to deliver innovative solutions that enhance operational efficiency and scalability.
Overview
11
11
years of professional experience
Work History
Software Engineer
Amazon Web Services (AWS)
Bellevue
03.2020 - Current
- Fleet-Wide Routing Intelligence Strategy – Spearheaded a multi-quarter migration from host-local routing heuristics to a centralized shared model across 10K+ hosts (1.8M TPS), preventing a projected 70% training signal loss. Led a team of 4 to architect a TB-scale distributed pipeline, performing rigorous risk analysis on data consistency and availability while evaluating real-time(cache based) vs. batch processing architectures to enable five 9s (99.999%) availability for scalable signal fusion. Successfully landed the model fleet-wide with 98% route estimation accuracy.
- Unified Multi-Fleet Log Search – Identified a critical org-wide debugging bottleneck and led a team of 3 to architect a self-service log search system supporting 60K+ queries/month; designed a partitioned S3-based log search system (Athena + Parquet) reducing projected costs from $1.07M/month to $12K/month (99% reduction) while maintaining sub-30s latency.
- Automated Spark Connectivity (re:Invent 2025 – AWS doc): Provided cross-functional leadership to set the technical direction for a unified Spark connectivity architecture between AWS Glue and Amazon SageMaker. Engineered a client library for automated credential resolution (IAM/Secrets) and vendor normalization across diverse federated catalogs—including Redshift, DynamoDB, Snowflake, and PostgreSQL—reducing connection setup time by 99% and eliminating manual configuration errors at enterprise scale.
- Supply Chain Logistics – Time-Space Graph Optimization – Reduced p99 latency by 10% and heap memory usage by 15% by redesigning the global routing engine’s graph search algorithm, pruning suboptimal paths and replacing an O(log n) PriorityQueue with an amortized O(1) ArrayDeque.
Associate
Delhivery Pvt Ltd
Gurugram
01.2015 - 01.2016
- Achieved 95%+ accuracy in logistics resource planning by developing linear regression models to forecast dispatch center load and optimize manpower allocation.
Education
Master of Science - Bioinformatics
Georgia Institute of Technology
Atlanta, GA01-2019
Bachelor of Technology - Biotechnology
NIT Jalandhar
Jalandhar, India01-2015
Skills
- Languages & Frameworks: Java, Python, SQL, TypeScript, C, Bash, Spring Boot, Hibernate
- System Design: Microservices, REST APIs, gRPC, Data Modeling, Caching, Sharding, Scalability, CAP Theorem
- AI-Assisted Development: Claude Code, Cursor, GitHub Copilot, MCP (Model Context Protocol)
- Big Data & Databases: Apache Spark, AWS Glue, Athena, EMR, SageMaker, Parquet, MySQL, PostgreSQL
- Cloud & Infrastructure: AWS (S3, DynamoDB, Lambda, SQS, SNS, IAM), Docker, CI/CD, Git, CloudFormation
- Javascript
Timeline
Software Engineer
Amazon Web Services (AWS)
03.2020 - Current
Associate
Delhivery Pvt Ltd
01.2015 - 01.2016
Master of Science - Bioinformatics
Georgia Institute of Technology
Bachelor of Technology - Biotechnology
NIT Jalandhar
Academic Experience
- Graduate Research Assistant | Advisor: Dr. John McDonald | Georgia Tech May 2019 – Dec 2019
- Received Faculty Research Award: Achieved 88%+ accuracy in chemo-response modeling via SVM-RFE and Information Gain feature selection on 56K+ genomic features using SVM/Random Forest classifiers.
- Analyzed RNA-seq gene patterns using PCA, K-means, and Hierarchical Clustering [GitHub].
- Graduate Teaching Assistant (Game Artificial Intelligence) | Georgia Tech Jan 2019 – April 2019
- Mentored students in algorithmic logic and A
- Search/behavior trees for optimized game state execution.