Hi, I build practical AI products
Applied AI · Product engineering · Intelligent systems
I work at the intersection of AI, product thinking, and engineering discipline to turn ideas into reliable experiences.
My focus is on building embedding-based search, retrieval systems, and production-ready AI features that are useful, measurable, and maintainable.
When I'm not shipping product work, I write about practical implementation choices on the blog.
Technical Skills
Core competencies honed across research and production environments.
Services Offered
I help teams move from prototype to production-ready AI systems.
Embedding Solutions
Custom embedding pipelines for semantic search, duplicate detection, recommendation, and similarity tasks — fine-tuned for your domain.
Model Selection
Rigorous benchmarking and evaluation to identify the best open-source or proprietary model for your specific task, latency, and budget constraints.
Pipeline Development
End-to-end ML pipelines: data ingestion, preprocessing, training, evaluation, deployment, and monitoring with modern MLOps practices.
RAG & Knowledge Systems
Retrieval-augmented generation systems that ground large language models in your proprietary documents and data sources.
AI Audits & Reviews
Independent review of existing AI systems for accuracy, latency, cost efficiency, and alignment with business objectives.
Workshops & Training
Hands-on workshops for engineering teams on embeddings, RAG, and production ML best practices.
Experience
Senior AI Engineer
Independent / Freelance
Designing and building embedding-based search systems and RAG pipelines for clients across legal, e-commerce, and SaaS domains.
ML Engineer
AI-driven Startup (Series A)
Built the core retrieval backbone for a knowledge management product; improved recall@10 from 65 % to 91 % by fine-tuning bi-encoder models.
Data Scientist
Enterprise Software Company
Developed NLP classifiers, entity extractors, and embedding-based clustering pipelines for document processing workflows.