I'm a software engineer who builds APIs, data pipelines, and ML systems in Python and TypeScript. At EarthCam, I re-architected the data-fetching layer of a core customer-facing component around asynchronous API calls, cutting load time from 15,000+ ms to 2,000-3,000 ms, a 3-5x improvement, and delivered new pages and features across the stack in TypeScript and Node.js.
On my own time, I build end-to-end ML systems: a fine-tuned LLM served behind a streaming FastAPI inference API with an automated evaluation gate, a ReAct-style agent with multi-turn memory and live reasoning-step streaming, and a feature engineering pipeline for financial transaction data with point-in-time correct serving and unit tests covering ingestion through serving.
At Cognitive Network Solutions, I developed end-to-end ML pipelines in Python for telecom network optimization: feature engineering with pandas and Polars, model training with PyTorch and graph neural networks, and GPU-accelerated inference tracked in MLflow. I built streaming data pipelines with Kafka for real-time network telemetry, and secured SQL and graph databases (PostgreSQL, Neo4j) integrated into Python microservices via SQLAlchemy, psycopg2, and FastAPI. I also run the infrastructure my software ships on: automating data-quality and security scans that gate every merge through GitLab CI/CD, and building GPU-accelerated training and inference workloads through the NVIDIA 6G Developer Program with auto-scaling batch jobs to manage compute costs.
Previously at Dfinitiv, I built cloud-native data pipelines on AWS and GCP that cut processing time by over 60%.
I'm looking for Software Engineer and Backend Engineer roles where I can build production software, backed by the platform experience to run it reliably.