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ML Engineer at G2i Inc.. Remote Location: Remote. Machine Learning Engineer (LLM Fine-Tuning) | Remote. Location:. Fully Remote. Contract Rate:. Up to . USD78/hour. About our Client. Our client helps business leaders make better strategic decisions through in-depth expert interviews and curated insights. Our mission is to transform the way executives access and apply real-world expertise.. We’re a small, highly technical, and product-focused team working to leverage AI to scale human expertise.. About the Role. We’re seeking a . Machine Learning Engineer. experienced in . fine-tuning and deploying Large Language Models (LLMs). . You’ll work closely with our product and data teams to build, refine, and operationalize intelligent systems that enhance how our users interact with expert insights.. This is a . hands-on engineering role. , ideal for someone who’s comfortable working autonomously and thrives in a fast-moving environment.. Responsibilities. Design, fine-tune, and deploy . LLMs. for natural language understanding, text generation, and summarization tasks.. Optimize existing ML models for performance, cost, and latency.. Build and maintain robust data pipelines for model training and evaluation.. Collaborate with cross-functional teams to integrate AI-driven features into production systems.. Continuously explore new techniques in . prompt engineering. , . retrieval-augmented generation (RAG). , and . model optimization. .. Requirements. Proven experience fine-tuning and deploying LLMs. (OpenAI, Anthropic, Mistral, LLaMA, etc.).. Strong background in . machine learning engineering. , with experience in Python and frameworks such as . PyTorch. , . TensorFlow. , or . Transformers. .. Solid understanding of . NLP. , . model evaluation. , and . data preprocessing. .. Experience building . end-to-end ML systems. , from data ingestion to deployment.. Familiarity with . MLOps. tools and . cloud infrastructure. (AWS, GCP, or Azure).. Excellent communication and documentation skills.. Nice to Have. Experience working with . vector databases. (Pinecone, Weaviate, FAISS).. Understanding of . RAG. , . prompt tuning. , or . instruction fine-tuning. .. Previous work in . content intelligence. , . research. , or . knowledge management platforms. .. Why Join . Work directly with a lean, high-impact team passionate about AI and product quality.. Fully remote and flexible working schedule.. Opportunity to influence the AI roadmap of a company transforming access to human expertise.