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Vetted Model Fine-tuning Professionals
Pre-screened and vetted.
Senior AI Engineer & Data Scientist specializing in LLM and RAG systems
Junior Full-Stack Software Engineer specializing in FinTech and AI systems
Intern Software Engineer specializing in LLMs, RAG, and Full-Stack Development
Mid-level Machine Learning Engineer specializing in LLM, RAG, and conversational AI systems
Junior Machine Learning Engineer specializing in LLMs, RAG, and multi-agent learning
Mid-level AI/Data Engineer specializing in LLM agents, RAG, and cloud data pipelines
Mid-level Data Scientist specializing in machine learning, computer vision, and generative AI
Mid-level AI/ML Engineer specializing in NLP, GenAI, and fraud/risk analytics
Senior Full-Stack Software Engineer specializing in AI-enabled microservices and micro-frontends
Mid-level AI/ML Engineer specializing in LLM, RAG, and agentic systems
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG for healthcare
Junior AI Engineer specializing in LLM systems, RAG, and production data pipelines
Shreevershith Kollabettu
Mid-level AI Engineer specializing in LLMs, agentic systems, and MLOps
“AI-focused engineer with Infosys experience building Azure/.NET chatbot applications and recent hands-on work with FastAPI/LangChain. Built a hackathon multi-agent legal counsel system showcasing agent orchestration, and emphasizes production readiness via Docker, GitHub Actions CI/CD, pytest automation, and adversarial simulations for auditable AI behavior. No direct robotics/ROS experience to date.”
Adithya Gururaj
Junior AI Engineer specializing in agentic AI, RAG, and voice/telephony systems
“LLM/agent engineer who has built production multi-agent systems (LangChain/LangGraph) for enterprise workflows like email and calendar automation, with a strong focus on latency, tool-calling accuracy, and evaluation via LangSmith. Also worked on AI long-term memory using knowledge graphs at VEAI and communicated the approach and tradeoffs to CEO/CTO stakeholders.”
Vamsidhar Vuddagiri
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and Azure
“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”
revanth polthi
Mid-level Data Scientist specializing in Generative AI and MLOps
“GenAI/LLM engineer with production experience at Allstate building an end-to-end document intelligence workflow for insurance operations—automating document intake, classification, and risk signal extraction. Emphasizes high-reliability design for regulated/high-stakes outputs using schema enforcement, confidence thresholds, validation rules, and human-in-the-loop routing, with metric-driven offline evaluation and production monitoring.”
Junior Robotics and Computer Vision Engineer specializing in perception and autonomy
Diana Minine Gudinho
Mid-level Data Scientist specializing in GenAI, RAG, and forecasting
“ML/NLP engineer focused on large-scale data linking for e-commerce-style catalogs and customer records, combining transformer embeddings (BERT/Sentence-BERT), NER, and FAISS-based vector search. Has delivered measurable lifts (e.g., +30% matching accuracy, Precision@10 62%→84%) and built production-grade, scalable pipelines in Airflow/PySpark with strong data quality and schema-drift handling.”