.png){kind=logo}
Vetted LLM Fine-Tuning Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and GenAI
Mid-level Data Scientist specializing in NLP, GenAI, and time-series modeling
Mid-level AI/ML Engineer specializing in real-time fraud detection and healthcare computer vision
Mid-level AI/ML Engineer specializing in recommender systems, MLOps, and Generative AI
Senior Generative AI & Machine Learning Engineer specializing in LLMs and MLOps
Mid-level Backend Software Engineer specializing in FinTech and scalable APIs
Mid-Level Software Engineer specializing in full-stack development and LLM/GenAI systems
Mid-level AI/ML Engineer specializing in scalable ML systems and cloud MLOps
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and deep learning
Senior Full-Stack & AI/ML Engineer specializing in cloud-native platforms and LLM systems
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
Matthew Mullins
Senior Software Engineer specializing in AI/ML backend and cloud infrastructure
“Backend/data platform engineer with production experience at Walmart and Molina Healthcare, building Python microservices on AWS (EKS + Lambda) for real-time inventory and recommendation systems. Strong in reliability/observability and incident leadership, plus modernizing legacy healthcare workflows and building resilient AWS Glue/PySpark pipelines with schema evolution and data quality controls.”
Alp Komban
Junior Machine Learning Engineer specializing in computer vision for medical imaging
“Applied ML/LLM practitioner working in healthcare-facing products, using RAG and LoRA fine-tuning on medical data and implementing production monitoring (confidence scoring) for clinician oversight. Has hands-on experience debugging agentic/LLM pipelines (including OCR preprocessing fixes) and regularly delivers technical demos to doctors, investors, and conferences—contributing to adoption and even helping close a funding round through end-to-end pipeline walkthroughs.”
Sayuj Shah
Mid-level Data Analyst & AI Practitioner specializing in ML, LLMs, and analytics platforms
“Data Analyst at U.S. Cellular who built production LLM solutions, including a Tableau-embedded chatbot that converts natural language questions into Oracle SQL and returns actionable KPI insights for non-technical users. Also authored MAD-CTI, a multi-agent LLM system for dark web hacker forum threat intelligence (published in IEEE Access) that outperformed single-agent approaches by 14%.”
Junior AI/ML Engineer specializing in LLMs, RAG, and multimodal agents
Mid-level Data Scientist specializing in ML, MLOps, and forecasting for FinTech and AI hardware
Junior AI Engineer specializing in computer vision, LLM infrastructure, and generative media pipelines
Intern AI/Data Science Engineer specializing in LLM agents, data engineering, and predictive analytics
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services