Job Url: https://www.remoterocketship.com/company/parkar-digital/jobs/ai-architect-data-background-united-states-remote Job Description: Parkar Digital Website LinkedIn All Job Openings Parkar Digital is a leader in transformative software solutions specializing in Azure-driven innovation. As a Microsoft Gold Partner, Parkar Digital empowers enterprises with AI Ops, Generative AI, and Machine Learning. They excel in providing advanced analytics, cloud modernization, application development, and IT operations optimization. Serving various industries, Parkar Digital offers tailored solutions in financial services, healthcare, manufacturing, and media to drive digital transformation and enhance operational efficiency. Their Vector platform and services enable businesses to leverage AI, cloud, and data analytics for sustainable growth and innovation. Product Development β€’ Application Engineering β€’ Integration β€’ Microservices β€’ API Marketplace 201 - 500 employees πŸ€– Artificial Intelligence 🏒 Enterprise ☁️ SaaS AI Architect - Data Background 13 hours ago πŸ‡ΊπŸ‡Έ United States – Remote ⏳ Contract/Temporary 🟑 Mid-level 🟠 Senior πŸ€– AI Engineer Airflow Amazon Redshift AWS Azure Cloud ETL Google Cloud Platform Kafka MongoDB NoSQL Postgres Python PyTorch Scikit-Learn SQL Tensorflow Apply Now Receive Emails with Similar Jobs Report problem πŸ“‹ Description β€’ We are seeking a highly skilled and visionary AI Architect with a strong data engineering background to design, implement, and optimize AI/ML solutions at scale. β€’ This role requires close collaboration with data engineers, scientists, and business stakeholders to architect intelligent systems that drive business outcomes. 🎯 Requirements β€’ Proven experience as an AI/ML Architect or Senior Data Architect with exposure to AI projects. β€’ Strong knowledge of data platforms such as Snowflake, MongoDB, PostgreSQL, Redshift, etc. β€’ Experience with Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn. β€’ Solid understanding of data modeling, ETL/ELT processes, data lakes, and data warehouses. β€’ Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker, Airflow). β€’ Excellent communication and leadership skills. β€’ Experience with cloud platforms such as AWS, Azure, or GCP.