Vijay Subramanya

Software Engineer

Bengaluru, Karnataka, India1 yr 2 mos experience

Key Highlights

8+ years of experience in scalable backend systems.
Expertise in machine learning and cloud-native applications.
Proven track record of high-impact, industry-grade systems.

Stackforce AI infers this person is a Backend Software Engineer with expertise in Healthcare and Data Engineering.

Contact

vijay.subramanya@gmail.com LinkedIn

Skills

Core Skills

Software DevelopmentProblem SolvingMachine Learning

Other Skills

AWSAlgorithmsAmazon Web Services (AWS)Apache SparkBackground ProcessingDatabase OptimizationDeep LearningDocker ProductsElasticsearchFlaskGitGoGo (Programming Language)GraphQLJSON

About

Software Engineer specializing in scalable backend systems and cloud-native applications, with additional expertise in applied machine learning. Experienced in designing and delivering production-ready services, building ML pipelines, fine-tuning models, and integrating solutions into full-stack platforms. Brings 8+ years of graph algorithms research and a proven track record of high-impact, industry-grade systems.

Experience

Activestate

Software Developer

Nov 2022 – Dec 2024 · 2 yrs 1 mo · Vancouver, British Columbia, Canada · Remote

Designed and implemented Git-like diff, merge and revert of syntax trees for an in-house version control system in Python, working closely with the clients and UX.
Reduced package dependency resolution response time from ~30s to 2s by implementing background processing in Go, improving user experience across 1,000+ daily builds.
Ran and debugged a migration of 500M+ version control records from S3 to Parquet using PySpark, reducing analytics query latency by ~40% and lowering storage costs.
Enhanced build request parsing logic to simplify JSON installer requests, improving maintainability and streamlining internal workflow.

PythonGoGitJSONBackground ProcessingPySpark+2

Kardioai

Software Engineer

Aug 2021 – Oct 2022 · 1 yr 2 mos · Toronto, Ontario, Canada

Designed and developed REST APIs in Go and Python to integrate deep learning models into production for automated cardiac CT scan analysis.
Built "Kardio Konnect," a plug-and-play Go tool for clients to securely de-identify, upload, and archive large medical datasets to AWS S3 with metadata in RDS; enabled ingestion of 2,000+ patient CT scans and reduced manual handling time by 90%.
Architected scalable backend services on AWS (S3, Lambda, RDS, EKS) and optimized database schemas for fast, reliable medical imaging metadata retrieval.

GoPythonAWSREST APIsDeep LearningDatabase Optimization+2

Acerta

Software Engineer Intern

May 2018 – Aug 2018 · 3 mos · Waterloo, Ontario, Canada

Developed a Python-based ingestion gateway to securely transfer high-volume manufacturing telemetry data from client plants to AWS EC2 for downstream processing.
Implemented Flask APIs for authentication, data uploads to AWS S3, and metadata management in RDS, enabling automated analysis workflows and reducing manual upload time by 80%.
Collaborated with the data science team to ensure backend services supported real-time analytics and could scale with growing sensor data volumes.

PythonFlaskAWSRDSSoftware Development