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Vetted LoRA Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in GenAI, RAG, and multi-agent systems
Mid-level AI Engineer specializing in agentic GenAI and cloud MLOps
Mid-level Machine Learning Engineer specializing in multimodal AI and anomaly detection
Mid-level Generative AI Engineer specializing in LLM orchestration, RAG, and agentic workflows
Mid-level AI & Data Engineer specializing in LLM compression, RAG, and agentic NLP systems
Mid-level AI/ML Engineer specializing in NLP, MLOps, and scalable ML platforms
Senior Data Scientist / ML Engineer specializing in NLP and Generative AI
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Mid-level AI/ML Engineer specializing in GenAI, computer vision, and real-time ML pipelines
Senior Full-Stack AI/ML Engineer specializing in personalization, NLP, and GenAI platforms
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Mid-level AI/ML Software Engineer specializing in Generative AI and NLP
Mid-level Software Engineer specializing in SRE, observability, and LLM-powered automation
Abnik Ahilasamy
Intern LLM/GenAI Engineer specializing in RAG, agentic systems, and low-latency inference
“Interned at Larsen & Toubro where they built and deployed an agentic RAG document question-answering system to reduce time spent searching documents and improve trustworthiness. Implemented ReAct-style multi-step orchestration with LangChain/LlamaIndex plus evidence-bounded generation, grounding/citations, and rigorous evaluation—cutting latency ~40%, hallucinations ~35%, and unsafe outputs ~40% while collaborating closely with non-technical business/ops stakeholders.”
Akshay Danthi
Senior AI Engineer specializing in production GenAI systems
“AI engineer who has shipped production LLM systems end-to-end, including a natural-language-to-SQL analytics copilot for career advisors that achieved ~95% query success through schema grounding, access controls, and automated regression testing with golden queries. Also builds LangGraph-orchestrated multi-step agents (resume analysis, recommendations) and RAG pipelines (PDF ingestion + FAISS) and partners closely with non-technical users to drive adoption and trust.”
Sanjesh Singh
Mid-Level Software Engineer specializing in embedded RTOS and applied AI
“Master’s student and Deep Learning teaching assistant who teaches LLM/VLM fine-tuning (including LoRA) and built a Hugging Face LLM fine-tuned for unit conversion, improving reliability by analyzing synthetic data and filling missing number-system conversion examples. Also implemented the Raft consensus protocol using gRPC in a distributed systems course with correctness validated by unit tests.”
Fnu Pallavi Sharma
Intern Data Scientist specializing in ML, NLP, and MLOps for healthcare and enterprise AI
“Built a production multi-cloud LLM-driven IT ticket automation system using LangGraph, Azure + Pinecone RAG, and an Ollama-hosted LLM on AWS, with Terraform-managed infra and PostgreSQL audit/state tracking for reliability. Also partnered with UW School of Medicine & Public Health students to deliver a glioma survival risk-ranking model, translating clinical feedback into practical pipeline improvements (imputation, site harmonization) and stakeholder-friendly visualizations.”