Satyam F.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

I'm a Python engineer with 8 years building production systems, now focused on AI and GPU-powered products. I currently lead engineering on a virtual try-on platform where I designed a multi-stage GPU pipeline — background removal, content gating, diffusion-based try-on, upscaling, and image-to-video — targeting 2–3 second inference on NVIDIA L4 GPUs. I architected the GPU workload system on Kubernetes using the GPU Operator, Kueue, KEDA, and Argo Workflows, and I lead a cross-functional team of backend, mobile, and QA engineers. Before this I worked on LLMs directly: I trained and evaluated models for code generation, engineered structured prompts, scored outputs against correctness benchmarks, and built web-scraping and search data pipelines to feed training. My backend foundation is deep. I've built analytics backends serving 500K+ records with sub-second query times, led a migration from a monolithic Django application to FastAPI microservices, built REST APIs with payment and authentication integrations, and tuned PostgreSQL queries and indexes. I'm comfortable owning a feature from requirements through to production. What I can do for you: - Build and optimize GPU inference pipelines (diffusion, image/video, LLMs) - Ship Python backends in FastAPI or Django with clean REST APIs and PostgreSQL - Deploy and scale AI workloads on Kubernetes (Docker, GPU Operator, KEDA, Argo) - Integrate LLMs and build the data pipelines around them I work 30+ hours/week and overlap with US and European business hours. If you're building something with AI at its core and need an engineer who can take it from prototype to production, message me — tell me what you're building and I'll tell you exactly how I'd approach it.