Work Experience

Technologies

Key Achievements

• •Achieved a 25% reduction in inference latency for a production-grade image generation pipeline by implementing advanced caching, torch compile, and float8 quantization, while integrating complex workflows including ControlNet, IP-Adapter, Inpainting, and LoRA
• •Created AI-powered game creation platform featuring a LangGraph-based coding agent with multi-agent architecture and RAG-powered context retrieval, enabling autonomous game generation and iterative refinement
• •Engineered production ML orchestration servers with Python, FastAPI and Pydantic, partnering closely with the frontend team to integrate NVIDIA A100 GPU-backed ML endpoints into the product with stable, well-specified request/response contracts and Azure cloud storage integration
• •Reduced infrastructure costs by implementing shared model caching across ML servers, eliminating redundant loads and optimizing GPU memory utilization
• •Accelerated ML development cycles by 2x with Gradio-based QA tooling, enabling rapid visual regression testing and real-time output comparison
• •Scaled synthetic data generation to 10,000+ samples/day using TypeScript/Puppeteer automation, eliminating manual orchestration across ML servers
• •Enabled semantic image search by building vector pipelines, replacing keyword-based retrieval with visual similarity matching, resulting in improved image search precision rate across the platform
• •Achieved 8x payload reduction for VLM segmentation masks via custom binary compression, cutting response latency and enabling real-time inference over Azure Service Bus
• •Iterated on the product by translating UX needs into ML-backed features with strong focus on latency, scalability, and maintainability

Technologies

Key Achievements

• •Designed and deployed scalable ETL pipelines on Google Cloud Platform using Dagster to process blockchain data at scale, delivering actionable user segmentation and persona insights that directly informed marketing strategy and product development roadmap.
• •Architected real-time analytics dashboard in Looker Studio monitoring 1-2M+ daily blockchain transactions, integrating BigQuery and PostgreSQL data sources to enable data-driven decision-making across operations, product, and executive teams.
• •Developed NFT recommendation engine using hybrid filtering algorithms and statistical analysis of user transaction history and NFT metadata, resulting in deeper insights of user persona.
• •Reduced fraud risk by building a Dagster-orchestrated anomaly detection system that automatically flagged suspicious blockchain transactions, with Neo4j graph visualizations to trace transaction patterns and track fraudulent activity networks.
• •Optimized SQL queries across BigQuery and PostgreSQL, reducing dashboard load times by 40% and enabling real-time monitoring of critical business KPIs.
• •Partnered with Product and Engineering teams to define key metrics and analytical frameworks, translating business questions into data models and delivering weekly insights presentations to leadership.

Technologies