Machine Learning Engineer (Databricks & Snowflake) | Remote | USC Only |

Xlysi LLC is a company specializing in advanced analytics and machine learning solutions. They are seeking a Machine Learning Engineer who will design, implement, and maintain analytics environments, focusing on advanced analytics, big data, and AI solutions while managing MLOps practices.

Responsibilities:

• Architect and build scalable ML pipelines using Databricks (PySpark, MLflow) and Snowflake (Snowpark, Streamlit, Cortex AI)
• Design and implement RAG and LLM-based solutions for enterprise data intelligence and automation
• Develop supervised (classification, regression) and unsupervised ML models for diverse business use cases
• Lead MLOps implementation including model versioning, CI/CD, automated testing, and monitoring (MLflow, Azure DevOps)
• Deploy and scale NLP/ML models into production with robust CI/CD pipelines and cross-team collaboration
• Build and optimize data pipelines for structured and unstructured data (Azure Data Factory, PySpark, SnowSQL)
• Tune Databricks and Snowflake environments for performance and scalability of AI/ML workloads
• Provide technical leadership and mentorship on ML best practices, LLM development, and cloud-native workflows
• Drive ML architecture, evaluate emerging technologies, and align solutions with enterprise goals
• Define development standards, collaborate with stakeholders, and architect enterprise-wide advanced analytics and data platforms

Requirements:

• Expertise in Snowflake architecture, performance tuning, and SQL optimization
• Experience with ETL/ELT tools (e.g., Azure Data Factory, Coalesce) and building scalable data pipelines
• Experience with LLM development (e.g., RAG, document summarization, chatbot integration using LangChain or LlamaIndex)
• Strong understanding of data warehousing, dimensional modeling, and cloud platforms (Azure, AWS, GCP)
• Proficiency in Python, SnowSQL, and automation using Snowflake's API and Snowpark
• Knowledge of BI tools (e.g., Power BI, Tableau, SSRS) and ML integration using Snowpark, Azure Machine Learning, Databricks, and Snowflake Streamlit
• Proficiency in MLOps, including MLflow, Azure DevOps, model monitoring, and alerting
• Familiarity with CI/CD pipelines and version control using Git
• Strong background in data science, machine learning, deep learning, and advanced statistical techniques
• Deep understanding of ML system design and industry-standard integration patterns for production AI
• Excellent written and verbal communication skills
• Experience in Deep Learning Libraries, such as tensorflow or pytorch
• Health care industry experience