About Me
An AI/ML engineer and data specialist with deep expertise in building robust machine learning systems, scalable data infrastructure, and modern MLOps solutions that drive real-world business impact.
Professional Journey
Currently leading Data Engineering, AI and MLOps initiatives at Droisys Inc., where I build high-performance computer vision and generative AI systems for large-scale retail analytics.
My recent work includes architecting multi-model vision pipelines, deploying advanced GPU-accelerated inference, and creating scalable MLOps solutions that power business growth for major clients.
I have designed end-to-end pipelines covering data collection, annotation, model training, and real-time deployment, enabling sales teams to extract actionable insights and automate key workflows.
Previously at NetApp, I developed core backend services, resolved customer-facing issues, and contributed to the reliability of major product releases.
Core Skills
Areas of Expertise
Data Engineering
Scalable pipelines, real-time and batch data processing, data lakes, and cloud warehousing.
Machine Learning
End-to-end model development for computer vision, NLP, generative AI, and large-scale deployment.
Analytics
Business intelligence, advanced reporting, and sales analytics using modern visualization tools.
Software Engineering
Full-stack app design (React, Node, .NET), API development, and production automation.
Infrastructure
Cloud-native architecture on AWS/GCP, containerization (Docker/Kubernetes), and MLOps automation.
Big Data
Distributed systems, high-performance batch/stream processing with Spark, and scalable data solutions.
Resume
My professional journey in software engineering, AI, and machine learning
Professional Experience
Data Engineer & AI/ML Lead
Led AI/ML system development for real-time shelf analytics and MLOps infrastructure overhaul across the company.
- Designed and implemented a real-time brand detection system using YOLOv7, achieving 25% higher accuracy and 80% faster training through multi-GPU optimization and advanced data augmentation techniques
- Engineered a scalable FastAPI-based REST service for real-time shelf analytics, processing 10,000+ images daily and contributing to 10-15% sales growth for retail clients
- Optimized model inference pipeline using NVIDIA Triton, reducing latency by 30% and enabling real-time processing of high-volume image streams
- Developed a generative AI pipeline leveraging Stable Diffusion and LoRA optimization, reducing ad campaign production time from weeks to hours (95% reduction)
- Created a document intelligence system using LangGraph and LangChain, enabling natural language querying of unstructured PDFs with 92% accuracy in information retrieval
- Modernized MLOps infrastructure with Kubernetes, MLflow, and DVC, reducing model training time by 60-70% while improving experiment tracking and reproducibility
- Built a high-throughput data processing pipeline using Apache Kafka, Airflow, and Spark, reducing data latency by 70% while handling 1M+ events per day
- Deployed and optimized on-premises LLM (DeepSeek) with FastAPI streaming, achieving sub-200ms response times for enterprise RAG applications
- Mentored junior engineers in ML engineering best practices, conducting bi-weekly knowledge sharing sessions on MLOps and LLM deployment strategies
MTS Software Engineer II
Worked on logging infrastructure and bug resolution in enterprise software systems.
- Developed end-to-end data protection and monitoring features for Snapcenter Plugin for VMware vSphere, contributing across full SDLC including design, development, testing, and production support
- Designed and implemented a scalable Audit Logging service using .NET and Entity Framework, delivering comprehensive system activity tracking and compliance reporting
- Led cross-functional collaboration to address over 3% of customer-reported bugs, significantly improving product reliability and customer satisfaction
- Spearheaded security compliance by managing Blackduck tooling, reducing vulnerability and license violations by 10%
- Authored technical documentation and conducted knowledge transfer sessions for product support and engineering teams, ensuring smooth feature adoption and release cycles
Education
Master of Science in Computer Science
Bachelor of Science in Computer Science
Technical Specializations
Get In Touch
I'm always open to discussing new opportunities, interesting projects, or just having a conversation about data engineering and AI/ML.