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Adarsh SM
@adarshsmr
GenAI Engineer for RAG Chatbots, LLM Fine tuning and AI Agents
India
Inglese, Hindi, Kannada, Telugu
Chi sono
I build AI that works in production, not just in demos. I'm an ML & GenAI engineer with 5+ years of experience shipping RAG chatbots, fine-tuned LLMs, computer vision and AI agents on AWS, GCP and Azure. Past work: AI systems for DRDO, a healthcare imaging model (95% accuracy) and finance automation (40% less manual work). You get clean, documented code, deployment and a walkthrough call. Message me before ordering: I reply within an hour and will tell you honestly if AI is the right fit.
Competenze
Adarsh SM
offline •
Tempo di risposta medio: 1 ora
Consulta i miei servizi
visione artificiale
I will build computer vision and predictive machine learning models
Sviluppo di chatbot IA
I will build a production ready rag chatbot on your documents and data
Portfolio
Esperienza lavorativa
Founder, Sigil (AI mobile app)
Self-Employed / Independent Developer • Lavoratore autonomo
May 2026 - Present • 5 mos
Founder of Sigil, an AI-native mobile app that turns spoken agreements into binding digital micro-contracts. - Small language models run entirely on-device, so the conversation never leaves the phone - Zero cloud round-trips, privacy-first by design Tools: on-device SLMs, speech processing, mobile.
AI Research Engineer / ML Engineer
stealth
Apr 2026 - Present • 6 mos
Core contributor to AURA, a ~30B-parameter dual-branch flow-matching diffusion transformer that generates 2K video with synchronised stereo audio in one forward pass. - Cut sampling from 50 steps to 8 or fewer via step distillation Tools: PyTorch, Diffusion Transformers, Rectified Flow, LCM.
ML Engineer & Gen AI Specialist (Direct Clients)
Self-Employed / Freelance • Freelance
Jan 2024 - Present • 2 yrs 9 mos
Freelance work with direct clients in finance, healthcare and developer tools, shipping LLM, RAG and computer vision systems. - Fine-tuned LLMs (GPT, BERT) for code generation and intent recognition: +30% contextual accuracy - Built RAG pipelines over financial documents with FAISS and Pinecone: 40% less manual effort - Built a radiographic analysis model (CNNs, transfer learning) with 95% accuracy that cut time to diagnosis by 40% Tools: PyTorch, GPT, BERT, FAISS, Pinecone.
