AI Data Engineer

Job Title: AI Data Engineer Location: San Francisco, CA (Hybrid)\` Duration: 3-6 Months CTH Experience: Minimum 12+ Years Job Description: • Design, build, and maintain large-scale data pipelines and architectures to support AI and machine learning initiatives. • Collaborate with data scientists, AI engineers, and analytics teams to ensure seamless data flow for model development and deployment. • Develop and optimize ETL processes to extract, transform, and load data from multiple structured and unstructured sources. • Build data platforms that enable high-performance AI/ML model training, testing, and monitoring. • Ensure data quality, integrity, and availability across all AI-driven systems. • Work with massive datasets to preprocess, cleanse, and structure data for analytics and machine learning applications. • Integrate cloud-based data services and tools to support large-scale AI workloads. • Automate data workflows and support the deployment of AI models using MLOps best practices. • Research and implement the latest advancements in data engineering and AI infrastructure technologies. Required Skills: • Minimum 12 years of experience in Data Engineering with a strong focus on AI/ML data systems. • Proficiency in programming languages such as Python, SQL, and Scala. • Strong experience with big data tools and frameworks such as Spark, Hadoop, Hive, and Kafka. • Hands-on experience with data pipeline orchestration tools like Airflow or Databricks. • Expertise in cloud platforms such as AWS, Azure, or Google Cloud (preferably with AI/ML services). • Solid understanding of data modeling, warehousing, and data lake architectures. • Experience integrating data for machine learning workflows and managing feature stores. • Familiarity with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. • Knowledge of MLOps tools like MLflow, Kubeflow, or DataRobot for production model deployment. • Strong understanding of APIs, REST services, and real-time data streaming solutions. Preferred Skills: • Experience with data governance, metadata management, and lineage tracking. • Familiarity with generative AI data preparation and LLM data pipelines. • Exposure to NLP, computer vision, or AI model integration within data systems. • Experience with CI/CD pipelines for data and AI model automation. • Excellent analytical, problem-solving, and communication skills. • Strong background in mathematics, statistics, or computer science fundamentals. Education: • Bachelor’s degree in Computer Science, Data Engineering, or related field required. • Master’s preferred.