ML Engineer
4 days ago
Job Description:
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.
- Bachelor's 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:
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.
- Bachelor's degree required
Preferred:
- LLM fine-tuning experience (LoRA, PEFT).
- Knowledge graph integration with LLMs.
- Familiarity with cloud ML deployment (AWS (preferred), Databricks, Azure).
- Master's 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.
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