LLM Data Engineer | United States | Fully Remote

Halo Media; Orlando (FL); Remote; USD 90,000 - 150,000; Full time

Job summary

An innovative company is on the lookout for an experienced AI/LLM Data Engineer to spearhead the development of cutting-edge data pipelines for a Generative AI platform. In this pivotal role, you will leverage your expertise in large language models and data engineering to design and implement robust data workflows. You will collaborate with cross-functional teams to deliver high-quality AI solutions while optimizing data storage and processing. If you have a passion for innovation and a commitment to ethical AI development, this is the perfect opportunity to make a significant impact in the field of AI.

Benefits

US employees benefit package

Qualifications

• 3-5 years of experience in data engineering, especially in AI/ML contexts.
• Strong understanding of LLM architectures and data requirements.

Responsibilities

• Design and maintain an end-to-end data pipeline for LLMs.
• Collaborate with teams to ensure data quality for AI/ML models.

Skills

Python

Data Engineering

LLM Technologies

Retrieval-Augmented Generation (RAG)

Data Cleaning

Problem-Solving

Communication

Education

Master's degree in Computer Science

Master's degree in Data Science

Tools

Snowflake

Apache Spark

Dask

LangChain

LlamaIndex

Semantic Kernel

OpenAI functions

Job description

We are seeking an experienced AI/LLM Data Engineer to build and maintain the data pipeline for our Generative AI platform. The ideal candidate will be well-versed in the latest Large Language Model (LLM) technologies and have a strong background in data engineering, with a focus on Retrieval-Augmented Generation (RAG) and knowledge-base techniques. This role sits in the AI COE within DX Tech & Digital. As a AI/LLM Data Engineer (you will report into the Director, AI Solutions & Development who oversees the AI COE.

You will work on highly visible strategic projects, collaborating with cross-functional teams

to define requirements and deliver high-quality AI solutions.

The ideal candidate will have a passion for Generative AI and LLMs, with a proven track record of delivering innovative AI applications.

Responsibilities
• Design, implement, and maintain an end-to-end multi-stage data pipeline for LLMs, including Supervised Fine Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) data processes
• Identify, evaluate, and integrate diverse data sources and domains to support the Generative AI platform
• Develop and optimize data processing workflows for chunking, indexing, ingestion, and vectorization for both text and non-text data
• Benchmark and implement various vector stores, embedding techniques, and retrieval methods
• Create a flexible pipeline supporting multiple embedding algorithms, vector stores, and search types (e.g., vector search, hybrid search)
• Implement and maintain auto-tagging systems and data preparation processes for LLMs
• Develop tools for text and image data crawling, cleaning, and refinement
• Collaborate with cross-functional teams to ensure data quality and relevance for AI/ML models
• Work with data lake house architectures to optimize data storage and processing
• Integrate and optimize workflows using Snowflake and various vector store technologies

Requirements

• Master's degree in Computer Science, Data Science, or a related field
• 3-5 years of work experience in data engineering, preferably in AI/ML contexts
• Proficiency in Python, JSON, HTTP, and related tools
• Strong understanding of LLM architectures, training processes, and data requirements
• Experience with RAG systems, knowledge base construction, and vector databases
• Familiarity with embedding techniques, similarity search algorithms, and information retrieval concepts
• Hands-on experience with data cleaning, tagging, and annotation processes (both manual and automated)
• Knowledge of data crawling techniques and associated ethical considerations
• Strong problem-solving skills and ability to work in a fast-paced, innovative environment
• Familiarity with Snowflake and its integration in AI/ML pipelines
• Experience with various vector store technologies and their applications in AI
• Understanding of data lakehouse concepts and architectures
• Excellent communication, collaboration, and problem-solving skills.
• Ability to translate business needs into technical solutions.
• Passion for innovation and a commitment to ethical AI development.
• Experience building LLMs pipeline using framework like LangChain, LlamaIndex, Semantic Kernel, OpenAI functions.
• Familiar with different LLM parameters like temperate, top-k, and repeat penalty, and different LLM outcome evaluation data science metrics and methodologies.

Preferred Skills

• Experience with popular LLM/ RAG frameworks
• Familiarity with distributed computing platforms (e.g., Apache Spark, Dask)
• Knowledge of data versioning and experiment tracking tools
• Experience with cloud platforms (AWS, GCP, or Azure) for large-scale data processing
• Understanding of data privacy and security best practices
• Practical experience implementing data lakehouse solutions
• Proficiency in optimizing queries and data processes in Snowflake or Databricks
• Hands-on experience with different vector store technologies

Benefits

• US employees benefit package.