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Vetted LoRA Professionals
Pre-screened and vetted.
Mid-level AI Engineer specializing in Generative AI and RAG systems
Mid-level Full-Stack Engineer specializing in Java/Spring Boot and cloud-native microservices
Junior Machine Learning Engineer specializing in LLM infrastructure and inference optimization
Mid-level AI/ML Engineer specializing in LLM, RAG, and agentic systems
Senior Software Developer specializing in cloud-native microservices and GenAI/ML
Mid-level Machine Learning Engineer specializing in Generative AI, LLMs, and MLOps
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Mid-level AI/ML Engineer specializing in Generative AI agents and workflow automation
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
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.”
Ravali Yerrapothu
Senior Machine Learning Engineer specializing in LLMs, RAG, and Computer Vision
“Built a production LLM-powered clinical note summarization and retrieval system that structures patient/provider/payer discussions into standardized outputs (symptoms, treatments, clinical codes, and prior-auth decisions) and stores notes as embeddings for hybrid search and proactive prior-authorization prediction. Experienced with LangChain/LangGraph orchestration, RAG, and grounding against medical code databases, and has communicated model feasibility/limitations to business stakeholders (Virtusa/Comcast).”
Sachin Kulkarni
Mid-level AI/ML Engineer specializing in LLMs, NLP, and AWS MLOps
“Recent master’s graduate in robotics with applied experience across reinforcement learning and ROS 2 autonomy stacks. Built an RL-based drone vertiport traffic controller (PPO) focused on reward design and simulation integration, and has hands-on navigation work in ROS 2 including LiDAR preprocessing, SLAM/path planning, and stabilizing TurtleBot3 wall-following. Also brings deployment experience containerizing robotics nodes and scaling them with Kubernetes on AWS.”
Mid-level Machine Learning Engineer specializing in LLMs, Generative AI, and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Generative AI Engineer specializing in LLM, RAG, and multimodal enterprise solutions
Mid-level AI Engineer specializing in LLM agents and production ML systems
Harshal J Hirpara
Mid-level Machine Learning Engineer specializing in LLM alignment and applied reinforcement learning
“AI/LLM engineer who has shipped production systems end-to-end, including a note-taking product (Notey) combining audio/image capture, ASR, summarization, and a semantic chat agent over past notes. Also has applied ML experience in healthcare, collaborating directly with doctors to validate an EEG seizure-detection pipeline, and uses Kubernetes to optimize GPU usage for LLM training.”
Monthir Ali
Senior AI/ML Engineer specializing in LLMs, RAG, and VR/XR multimodal systems
“PhD researcher (University of Utah) who built a production RAG-powered Virtual Reality Research Assistant to answer lab research questions with concrete citations. Implemented an end-to-end LangChain pipeline using PyPDFLoader, chunking strategies, OpenAI embeddings, and ChromaDB, with emphasis on grounding to reduce hallucinations and ensure research-grade accuracy. Collaborated closely with a non-technical PhD advisor to scope requirements, manage cost constraints, and demo iterative progress.”