Data Engineer - LLM

HTC Global Services wants you. Come build new things with us and advance your career. At HTC Global you'll collaborate with experts. You'll join successful teams contributing to our clients' success. You'll work side by side with our clients and have long-term opportunities to advance your career with the latest emerging technologies. At HTC Global Services our consultants have access to a comprehensive benefits package. Benefits can include Paid-Time-Off, Paid Holidays, 401K matching, Life and Accidental Death Insurance, Short & Long Term Disability Insurance, and a variety of other perks. 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. 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 Qualifications 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