Machine Learning Hardware Engineer

iFlow Inc.; Normal (IL); On-site; USD 85,500 - 95,800; Full time

Job summary

A leading technology company in Normal, IL is seeking a Staff LLM–RAG Engineer to optimize enterprise-grade AI solutions. The role demands extensive experience in software engineering and applied AI/ML, specifically in large language models and retrieval systems. Ideal candidates should hold a Bachelor's degree and exhibit strong proficiency in Python and Golang. Join us to drive innovation in AI technology in a collaborative environment.

Qualifications

• 8+ years in software engineering or applied AI/ML.
• 2+ years focused on LLMs and retrieval systems.
• Hands-on experience with vector databases.

Responsibilities

• Lead RAG Architecture Design for retrieval systems.
• Build and optimize multi-stage pipelines.
• Develop services and APIs in Python and Golang.
• Implement hybrid search and embedding optimization.
• Design prompts for domain-specific applications.

Skills

Python

Golang

RUST

RAG frameworks (LangChain, LangGraph, LlamaIndex)

Vector databases (Databricks, Pinecone, Weaviate, Milvus, Chroma)

Problem-solving

Communication

Education

Bachelor's degree

Master's or PhD degree in CS (preferred)

Job description

4 days ago Be among the first 25 applicants

We are seeking a Staff LLM–RAG Engineer (Contract) to lead the development and optimization of enterprise-grade retrieval-augmented generation systems. You will architect scalable AI solutions, integrate large language models with advanced retrieval pipelines, and ensure production readiness. This role combines deep technical expertise with the ability to guide teams and deliver results on aggressive timelines.

Most Important Skills/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.
• Bachelors degree required
• Strong proficiency in Python and Golang or RUST, with experience building high-performance services and APIs.
  
  

Key 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.
  
  

Qualifications

Must Have:

• 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).
• Strong understanding of hybrid search (semantic + keyword) and embedding optimization.
• Bachelors degree required
  
  

Preferred

• LLM fine-tuning experience (LoRA, PEFT).
• Knowledge graph integration with LLMs.
• Familiarity with cloud ML deployment (AWS (preferred), Databricks, Azure).
• Masters or PHD degree in CS
  
  

Soft Skills

• Strong problem-solving and decision-making skills under tight timelines.
• Excellent communication for cross-functional collaboration.
• Ability to work independently while aligning with strategic goals.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  IT Services and IT Consulting

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