Halo Media
LLM Data Engineer | United States | Fully Remote
Halo Media, New York, New York, United States,
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.
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.