Motion Recruitment
Machine Learning Hardware Engineer
Motion Recruitment, Oklahoma City, Oklahoma, United States, 73116
Overview
Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now. Fantastic opportunity with a growing EV auto manufacturer for a Staff LLM–RAG Engineer (Contract) to lead the development and optimization of enterprise-grade retrieval-augmented generation systems. This is a 100% remote contract opportunity.
Location: Remote (Central Time). Duration: 12+ months to start.
Responsibilities
Lead RAG Architecture Design – Define and implement best practices for retrieval-augmented generation systems, ensuring reliability, scalability, and low-latency performance.
Full-Stack AI Development – Build and optimize multi-stage pipelines using LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, or custom).
Programming & Integration – Develop services and APIs in Python and Golang to support AI workflows, document ingestion, and retrieval processes.
Search & Retrieval Optimization – Implement hybrid search, vector embeddings, and semantic ranking strategies to improve contextual accuracy.
Prompt Engineering – Design and iterate on few-shot, chain-of-thought, and tool-augmented prompts for domain-specific applications.
Mentorship & Collaboration – Partner with cross-functional teams and guide engineers on RAG and LLM best practices.
Performance Monitoring – Establish KPIs and evaluation metrics for RAG pipeline quality and model performance.
Ideal Background
8+ years in software engineering or applied AI/ML, with at least 2+ years focused on LLMs and retrieval systems.
Strong proficiency in Python and Golang or Rust, with experience building high-performance services and APIs.
Expertise in RAG frameworks (LangChain, LangGraph, LlamaIndex) and embedding models.
Hands-on experience with vector databases (Databricks Vector Store, Pinecone, Weaviate, Milvus, Chroma).
Seniority level
Mid-Senior level
Employment type
Contract
Job function
Information Technology
Industries
Information Services
#J-18808-Ljbffr
Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now. Fantastic opportunity with a growing EV auto manufacturer for a Staff LLM–RAG Engineer (Contract) to lead the development and optimization of enterprise-grade retrieval-augmented generation systems. This is a 100% remote contract opportunity.
Location: Remote (Central Time). Duration: 12+ months to start.
Responsibilities
Lead RAG Architecture Design – Define and implement best practices for retrieval-augmented generation systems, ensuring reliability, scalability, and low-latency performance.
Full-Stack AI Development – Build and optimize multi-stage pipelines using LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, or custom).
Programming & Integration – Develop services and APIs in Python and Golang to support AI workflows, document ingestion, and retrieval processes.
Search & Retrieval Optimization – Implement hybrid search, vector embeddings, and semantic ranking strategies to improve contextual accuracy.
Prompt Engineering – Design and iterate on few-shot, chain-of-thought, and tool-augmented prompts for domain-specific applications.
Mentorship & Collaboration – Partner with cross-functional teams and guide engineers on RAG and LLM best practices.
Performance Monitoring – Establish KPIs and evaluation metrics for RAG pipeline quality and model performance.
Ideal Background
8+ years in software engineering or applied AI/ML, with at least 2+ years focused on LLMs and retrieval systems.
Strong proficiency in Python and Golang or Rust, with experience building high-performance services and APIs.
Expertise in RAG frameworks (LangChain, LangGraph, LlamaIndex) and embedding models.
Hands-on experience with vector databases (Databricks Vector Store, Pinecone, Weaviate, Milvus, Chroma).
Seniority level
Mid-Senior level
Employment type
Contract
Job function
Information Technology
Industries
Information Services
#J-18808-Ljbffr