Machine Learning Engineer

Role Overview

Machine Learning Engineer working under the Director, Enterprise Architecture to build supervised and unsupervised AI/ML models.

Responsibilities

• Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud using Snowpark.
• Develop solutions using modern AI/ML/NLP techniques and rigorous statistical analysis.
• Use LLMs and Generative AI to enable software automation integrations.
• Build and operationalize Retrieval-Augmented Generation (RAG) frameworks.
• Enhance, develop, and deploy production-level ML models and algorithms to improve business outcomes and customer experience.
• Perform data cleansing, analysis, and feature engineering with Python.
• Work with multiple data types/sources (structured, semi-structured, unstructured) and assess data source effectiveness.
• Support model lifecycle activities: design, implementation, validation, calibration, documentation, product implementation, monitoring, and reporting.
• Communicate results clearly, with emphasis on data visualization.
• Collaborate with Data Scientists, Data Engineers, and Data Architects.
• Stay current with industry trends in AI/ML.
• Provide on-call support.

Requirements

• Master’s degree in a quantitative/applied field (e.g., Engineering, Computer Science, Data Science, Operations Research, Mathematics, Statistics, Econometrics).
• Strong experience manipulating and analyzing large datasets (exploratory analysis, model fitting, visualization).
• Proficient in SQL and working with large datasets (including big data/IoT).
• Proficient in Python for programming and modeling.
• Knowledge of pre-training and fine-tuning foundation LLM models.
• Experience with LangChain and sentence transformers.
• Knowledge of ChatGPT-4 (or comparable models).
• Experience applying current machine learning techniques and evolving data science best practices.