100% REMOTE: Machine Learning Engineer

Location: Remote (U.S.-based - cannot provide sponsorship for this role)
Type: Full-time | Direct Hire
Compensation: $160K–$300k+ (flexible for the right candidate)

About the Role

Our client is a forward-thinking AI company building next-gen products powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). They are actively looking for a Machine Learning Engineer with hands-on experience building LLM pipelines and implementing RAG architectures in production.

You’ll lead the development of scalable, intelligent systems that combine unstructured data with cutting-edge AI to deliver real-time insights and automation.

What You’ll Do

• Architect, build, and deploy end-to-end systems using LLMs and RAG

• Design intelligent document or data retrieval workflows using vector databases and embedding models

• Own implementation of LangChain, LlamaIndex, or similar tools to orchestrate RAG flows

• Integrate external APIs (OpenAI, Claude, Mistral, etc.) and optimize model selection, prompting, and performance

• Collaborate with backend and data engineers to ship reliable, scalable ML features

• Continuously improve retrieval precision and model relevance with feedback loops

Tech Stack

• Python, PyTorch, Hugging Face, LangChain, LlamaIndex

• Vector DBs: Pinecone, Weaviate, FAISS, Qdrant

• OpenAI, Anthropic, LLaMA, Mistral APIs

• AWS / GCP / Azure ML environments

Requirements

• 3+ years of ML Engineering experience (can include backend-heavy ML roles)

• Proven experience working with LLMs and building RAG pipelines

• Deep understanding of embeddings, semantic search, and vector databases

• Ability to design and deploy production-level ML systems

• Strong software engineering fundamentals