Senior AI/ML Data Engineer

Job Title: Senior AI/ML Data Engineer

Location: 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.