Top Remote Artificial Intelligence Data Engineering Jobs in San Francisco, CA

The Data Infrastructure Engineer will centralize data capabilities, improve data pipeline architecture, and ensure efficient data access across teams while optimizing GCP usage.

As the Senior Data Engineer for Enrichment, you'll design data pipelines, maintain contact datasets, ensure data quality, and optimize vendor relationships while working with a talented team.

The Research Engineer will advance decentralized AI by optimizing distributed training, developing open-source tools, publishing research, and enhancing platform capabilities.

The Senior/Staff Applied Scientist at Glean will enhance document indexing and retrieval algorithms, manage A/B testing platforms, and evaluate generative AI use cases, leveraging strong statistical and machine learning skills.

The Senior Data Engineer will design and maintain scalable data pipelines, lead medium-sized platform projects, and ensure reliability of data systems through monitoring and optimization. Responsibilities include working with cross-functional teams to improve data workflows and participate in incident response.

Lead architecture and design of scalable Data Lakehouse solutions on GCP, collaborating with clients on data challenges and technical requirements, while ensuring data governance and quality.

The Founding Platform/Infra Engineer will design and manage infrastructure, improve system observability and CI/CD processes, enhance security, and boost developer efficiency at Coverbase.

As a Staff Product Analytics Engineer, you will build and maintain data infrastructure, collaborate across teams to enhance product data use, and develop tools for data self-service.

The Analytics Engineer will enhance BI infrastructure, collaborate with Data Engineering, and deliver analytics-ready data. Responsibilities include managing Snowflake, dbt projects, and CI/CD workflows, optimizing data structures, and supporting BI initiatives.

As an Associate Technical Architect, you will solve big data problems and develop solutions for migration, storage, and processing, focusing on Databricks and data engineering.