Riverstart Document AI
R&D for source-linked specialist review: document extraction, deterministic checks and retrieval over reference material.
Senior ML Engineer
Computer vision, document AI and agentic systems, from R&D to maintained products.
Senior ML Engineer in Riverstart’s R&D ML team, working on document intelligence and engineering analysis. Previously shipped mobile and cloud computer vision at Carb Manager and developed financial-document recognition at CFT.
R&D for source-linked specialist review: document extraction, deterministic checks and retrieval over reference material.
Skin-analysis computer vision for Dermaself, connecting guided mobile capture with pore and wrinkle segmentation and usable results.
A published Python SDK and CLI for inspecting model runtime and applying inference optimizations within existing ML workflows.
A maintained Telegram service that helps people keep a food diary with meal photos, voice messages and text.
Research on turning point clouds into room models and 2D plans, alongside mechanical CAD projection and drawing analysis.
Inspect the generated room floor plan (SVG) · Inspect the inferred room geometry (JSON)
Video search case study combining keyframes, ASR/OCR, object and face signals, visual embeddings, transcript embeddings, and hybrid retrieval.
OCR, detection, segmentation and multimodal retrieval, from model experiments to server and on-device inference.
Hybrid retrieval, source-linked answers and human review for document and tool-based workflows.
Profiling, model packaging, evaluation and deployment across cloud and mobile.
Python, PyTorch, OpenMMLab, OpenCV, ONNX Runtime, FastAPI, OCR, retrieval, LLM/VLM systems, Docker, ClearML, Cloud Run