Senior AI/ML Data Engineer
4 weeks ago
About the job Senior AI/ML Data Engineer Job Title: Senior AI/ML Data EngineerLocation: California (Onsite) Job Type: C2C Position Overview We are seeking a highly skilled Senior AI/ML Data Engineer with expertise in multimodal AI models, vector databases, and Azure-based data engineering solutions. The candidate will lead design and implementation of scalable AI-driven data platforms, integrating advanced ML pipelines with modern cloud architectures. This is a client-facing, onsite role in California, requiring both technical depth and leadership ability to deliver enterprise-grade AI/data solutions. Key Responsibilities Design, build, and optimize AI/ML pipelines using multimodal models (CLIP, BLIP, Whisper, or similar) Implement vector database solutions (FAISS, Milvus, Weaviate) and embedding pipelines for retrieval-augmented systems. Develop and maintain data ingestion, ETL, and streaming solutions using Microsoft Fabric, Azure Data Factory, Event Hub, and Kafka. Architect, implement, and optimize Azure-based solutions, including Azure Synapse, Databricks, and Azure SQL. Write efficient SQL, Python, and Spark code for data transformation, ML feature engineering, and analytics. Use infrastructure-as-code (Terraform, ARM templates) for automated deployment and environment consistency. Collaborate with cross-functional teams (data science, cloud, and business stakeholders) to translate requirements into scalable solutions. Ensure data governance, compliance, and security best practices are applied across all platforms. Required Skills & Qualifications Hands-on experience with AI/ML multimodal models (CLIP, BLIP, Whisper, or similar). Strong proficiency in Python for AI/ML and automation workflows. Experience with vector databases (FAISS, Milvus, Weaviate) and embedding pipelines. Proficiency in Microsoft Azure services: Azure Data Factory Azure Synapse Azure Databricks Azure SQL Event Hub Experience in data streaming platforms (Azure Event Hubs, Kafka). Strong skills in SQL and Spark for large-scale data engineering. Experience with infrastructure-as-code (Terraform, ARM templates). Strong problem-solving, debugging, and performance optimization skills. Excellent communication skills with ability to mentor junior engineers and engage with stakeholders. Nice to Have Experience with Oracle PL/SQL and hybrid database ecosystems. Knowledge of data warehousing, data modeling, and governance frameworks. Exposure to MLOps frameworks and enterprise-grade AI deployment.
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