US LBM AI Engineer

US LBM•Remote-Texas, TX

19h

About The Position

The US LBM AI Engineer will help drive US LBM's initiatives and provide meaningful insight to deliver business value. As a member of the US LBM Enterprise Data and Analytics team, you help cultivate the culture of data-driven decision-making across our business. From business analytics to demand planning to pricing optimization to purchasing decisions, the Analytics team brings the power of our extensive data assets and capabilities to bear on US LBM's important decisions. As an AI Engineer at US LBM, you will leverage your analytical skills and expertise in AI & data science to help with sales, pricing, optimize supply chain, improve inventory management, logistics, enhance customer insights, and support strategic business decisions. You will work closely with cross-functional teams, including operations, finance, sales, and supply chain to turn data into actionable insights.

Requirements

Bachelor's Degree or Master’s degree in AI, Data Science, Computer Science, Statistics,Mathematics, or a related field.
3+ years of experience working in Data science/AI roles.
Working knowledge of large data set manipulation using SQL.
Hands-on experience with state-of-the-art LLMs such as GPT-3, GPT-4, BERT, T5, etc.
Python, SQL, Pandas, NumPy; Computer Vision (OpenCV, TensorFlow, PyTorch).
Experience with OCR tools (Tesseract, AWS Textract, Google Vision API), document layout is a plus.
Object detection (YOLO, MMDetection, Faster R-CNN, Detectron2) models.
API development and microservices architecture (FastAPI/Flask) and async processing.
Prompt engineering and experience with any of LlamaIndex, LangChain/LangGraph, Google ADK, PydanticAI.
Exposure to reporting tools using Tableau.
Machine Learning - Experience in Supervised/unsupervised learning; time-series forecasting is a plus.
Deployment & Infrastructure - AWS/Azure/GCP; Docker, Kubernetes; Torch Serve/TensorFlow Serving; ONNX Runtime.
Preferred Technology - CI/CD pipelines, Git; REST APIs; PostgreSQL/MySQL for metadata storage.
Strong problem-solving, analytical thinking, and communication.

Nice To Haves

document layout is a plus
time-series forecasting is a plus

Responsibilities

Partner with business stakeholders to gather requirements and translate them into technical specifications and process documentation for IT counterparts.
Conduct exploratory data analysis to identify patterns, anomalies, and relationships within the data.
Apply statistical techniques to test hypotheses and validate models.
Develop and train machine learning models to solve specific business problems (e.g., classification, regression, clustering etc.).
Build predictive models to forecast future trends, such as demand forecasting, customer behavior prediction, product recommendation etc.
Integrate LLMs into existing data pipelines and business processes.
Develop custom algorithms and tools to address specific business challenges.
Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence.
Experiment with new techniques and technologies to enhance analytical capabilities
Image & Document Processing - Build computer vision models, OCR, and parsing techniques for images and PDFs. Train object detection models (YOLO, MMDetection).
LLM-Based Component Extraction - Use Large Language Models (LLMs) to interpret extracted data. Develop prompt engineering strategies.
Data Engineering & Integration - Develop scalable pipelines for image processing and CRM integration. Implement APIs and microservices for real-time data exchange.
Sales Forecasting (Future Scope) - Create predictive models for sales trends and pricing using time-series and ML. Optimize models for accuracy, speed, and scalability; ensure robust validation.
Perform other duties as assigned.
Comply with all policies and standards.
Adhere to Company’s commitment to workplace safety.
Participate in and complete assigned trainings.