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Vetted LoRA Professionals
Pre-screened and vetted.
Akhilesh Patil
Junior AI/ML Engineer specializing in FinTech and generative AI
“Built an end-to-end AI bug triage dashboard that combined React/TypeScript, FastAPI, Postgres, and classical ML to reduce manual engineering triage work by about 40%. Stands out for pragmatic, product-minded AI engineering: choosing interpretable models when they were sufficient, designing human-in-the-loop UX for trust, and separately building an agentic RAG project with vector search, Neo4j knowledge graphs, and reranking.”
Tanuja Ikkurthi
Mid AI/ML Engineer specializing in LLM systems and Generative AI
“Built and owned an LLM support copilot at Stripe focused on improving agent ticket resolution. Designed the backend and ML system end to end, using RAG, Redis caching, hybrid vector search, and LoRA fine-tuning to achieve 40% lower latency and 22% higher response accuracy, with continuous quality monitoring via Ragas and related evaluation frameworks.”
Lakshmi Narayana
Mid-level Data Science AI/ML Engineer specializing in Generative AI, LLMs, and RAG systems
“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and recommendation systems
Junior Software Engineer specializing in AI/ML systems and LLM-powered document automation
Entry-Level Data Scientist specializing in Applied Analytics and Machine Learning
Intern Software Engineer specializing in full-stack web development and IoT/embedded systems
Senior AI/ML Developer specializing in LLMs, RAG, and generative AI
Mid-level Data Scientist / ML Engineer specializing in NLP, recommender systems, and insurance analytics
Mid-level AI/ML Engineer specializing in RAG systems and cloud data platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Junior AI Engineer specializing in LLM agents and RAG for energy operations
Mid-level Machine Learning Engineer specializing in recommender systems and LLM/RAG pipelines
Mid-level Data Scientist specializing in NLP, deep learning, and big data analytics
Mid-level AI/ML Engineer specializing in LLM evaluation, RAG, and GPU-accelerated inference
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Mid-level Software Engineer specializing in cloud-native AI/ML and full-stack systems
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”