Key Responsibilities

• Design, build, and deploy machine learning and deep learning models at scale
• Develop and maintain ETL/ELT pipelines using Spark and Databricks
• Implement and manage ML workflows using MLflow and Delta Lake
• Work with Generative AI, Large Language Models (LLMs), and RAG architectures
• Build and integrate Vector Databases for AI-powered applications
• Deploy and monitor ML models using AWS SageMaker and MLOps best practices
• Collaborate with data engineering teams to ensure robust data infrastructure
• Write optimized SQL and Python code for data analysis and model development

Requirements

• 8+ years of hands-on Data Science and Machine Learning experience
• Strong proficiency in Python and SQL
• Experience with Apache Spark and Databricks
• Hands-on experience with AWS cloud services
• Proficiency in ETL/ELT pipeline development
• Experience with MLflow for experiment tracking and model management
• Familiarity with Delta Lake architecture
• Experience with AWS SageMaker for model training and deployment
• Knowledge of Generative AI, LLMs, and RAG (Retrieval-Augmented Generation)
• Experience with Vector Databases (e.g., Pinecone, Weaviate, Chroma)
• Strong Data Engineering and MLOps background
• W2 employment authorization required — no C2C or 1099

Skills Required