AI / Machine Learning Consultant

---

AI / Machine Learning Consultant Needed for Online Resale Pricing & Market Prediction System I'm seeking an experienced AI / Machine Learning consultant to help explore and evaluate the feasibility of building a predictive decision-making system for an online resale business. Our business model relies on analyzing market movements, pricing trends, and external signals (social media, product announcements, news, etc.) to make profitable purchasing and pricing decisions. I’m looking to explore how AI—specifically models like XGBoost, LSTMs, Transformers, and LLMs (e.g., DeepSeek, Mistral, Llama)—can be combined or structured to improve this decision-making process over time. Key Objectives for the Consultation: ✅ Discuss the viability of building a hybrid AI model (LLM + LSTM/Transformer/XGBoost) ✅ Explore how reinforcement learning could be used to help models learn from actual resale outcomes ✅ Advise on best practices for handling incomplete and unstructured data ✅ Recommend approaches for data collection (APIs vs. scraping) for social signals (Twitter/X, Google Trends, Reddit, etc.) ✅ Assess the technical requirements for local deployment (hardware, software stack) ✅ Provide insights on how to continuously improve the model over time with feedback loops ✅ Suggest an implementation roadmap if the project is feasible Ideal Candidate: Proven experience with machine learning models for price prediction, forecasting, or trading systems Strong understanding of LLMs (e.g., DeepSeek, Mistral, Llama 3) and sequence models (LSTM, GRU, Transformers) Familiar with reinforcement learning techniques (RLHF, bandit models, Q-learning) Experience integrating external signals (social media, music streaming metrics, sentiment analysis) into predictive models Ability to explain complex technical concepts clearly to a non-developer with basic programming/system admin knowledge Knowledge of on-premise AI deployment considerations (GPUs, storage, local LLM hosting) Deliverables: A 1 hour consultation call Follow-up recommendations document summarizing the key findings, potential approaches, and next steps Bonus Skills (Preferred but Not Required): Knowledge of online resale markets, e-commerce, or financial modeling Familiarity with LangChain, LlamaIndex, Haystack, ChromaDB, or similar frameworks Understanding of vector databases and RAG (Retrieval Augmented Generation) models

Keyword: Machine Learning

Machine Learning Artificial Neural Network Artificial Intelligence TensorFlow