Karthik Vanga

Engineer with expertise in designing scalable data pipelines for large-scale image and metadata streams. Proven track record in developing backend services that orchestrate model inference and ensure high availability in distributed systems. Skilled in C++, Python, and Go, with a focus on translating raw model outputs into accurate inventory signals through robust data modeling

Software Engineer at Ford Motors (2025-08 – Present)

• Scalable Data Pipelines: Designed and maintained robust pipelines ingesting large-scale image and metadata streams, transforming raw data into structured inventory signals for 10M+ daily records.
• Backend Service Development: Developed backend services in Go and Python to orchestrate model inference, reducing prediction latency by 40% through optimized batching and caching strategies.
• System Reliability: Ensured 99.99% availability for distributed systems handling high-throughput data by implementing fault-tolerant architectures and comprehensive monitoring solutions.
• Data Modeling: Designed data models that translated raw model outputs into accurate inventory insights, improving signal consistency by 25% and reducing downstream error rates.
• Cross-Functional Collaboration: Partnered with Machine Learning Engineers and Data Scientists to integrate systems end-to-end, defining requirements that improved the usability of inventory signals for mobile and product teams.

Software Developer at CVS Health (2021-08 – 2023-12)

• Scalable Data Pipelines: Designed and maintained robust pipelines ingesting large-scale image and metadata streams, transforming raw data into structured inventory signals for 10M+ daily records.
• Backend Service Development: Developed backend services in Go and Python to orchestrate model inference, reducing prediction latency by 40% through optimized batching and caching strategies.
• System Reliability: Ensured 99.99% availability for distributed systems handling high-throughput data by implementing fault-tolerant architectures and comprehensive monitoring solutions.
• Data Modeling: Designed data models that translated raw model outputs into accurate inventory insights, improving signal consistency by 25% and reducing downstream error rates.
• Cross-Functional Collaboration: Partnered with Machine Learning Engineers and Data Scientists to integrate systems end-to-end, defining requirements that improved the usability of inventory signals for mobile and product teams.

Junior Software Engineer at First Dot IT (2020-12 – 2021-08)

• Built microservice architectures using Java and C++ to process high-volume data streams, achieving a 3x increase in throughput.
• Optimized SQL queries and database schemas to support low-latency access to structured data, reducing query times from seconds to milliseconds.
• Implemented debugging and monitoring tools for production services, decreasing mean time to resolution (MTTR) by 50%.

Master of Science in Computer Science – Saint Leo University

Bachelor of Technology in Electronics & Communication Engineering – TKR College of Engineering & Technology