Remote Data Jobs • US

As an AI Tutor - Statistics Specialist, you’ll play a key role in advancing xAI’s mission by enhancing our AI technologies through high-quality inputs, labels, and annotations using specialized software. You’ll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance.

Implement and support systems that reliably provide interactive query performance on large amounts of multi-modal data. You will collect, parse, analyze, and visualize large sets of data, improve systems that handle scale, and troubleshoot and improve the infrastructure required for data extraction, transformation, and loading from various data sources.

The ideal candidate can independently deliver reporting and analysis reliably. A Data Analyst takes initiative through identifying gaps and opportunities. They make good decisions within their scope without seeking guidance by leveraging technical knowledge and analytical skills to gather, clean, and analyze complex datasets. They employ statistical techniques to interpret and validate data trends, patterns, and anomalies and collaborate with cross-functional teams to understand project requirements.

The Senior Data Engineer will architect, implement, and optimize data models, pipelines, and storage solutions across Acquisition.com’s data ecosystem. This individual will ensure reliability, performance, and accessibility of data, serving as a bridge between raw information and actionable business intelligence. With a lean, agent-driven development paradigm, you will take complex data initiatives from concept to delivery.

As an AI Tutor - Materials Science Specialist at xAI, you will enhance cutting-edge AI technologies by providing high-quality input and labels using specialized software. You'll collaborate with our technical team to support the training of new AI tasks, contributing to innovative initiatives. Responsibilities include refining annotation tools and selecting complex problems from advanced materials science fields to drive improvements in model performance.

Design, develop, and maintain data pipelines that ingest, transform, and load data from various sources into data lakes, data warehouses, and data marts using Python, Spark and other cloud services to serve analytics needs and machine learning model requirements. Contribute to the detailed design and architecture of the data platform ensuring consistency, efficiency and reusability of data components and processes.

As a Biology Specialist at xAI, you will be instrumental in enhancing our cutting-edge AI technologies by providing high-quality input and labels using specialized software. You will collaborate closely with our technical team to support the training of new AI tasks, contributing to innovative initiatives. Your responsibilities include refining annotation tools and selecting complex problems from advanced biological fields to drive significant improvements in model performance.

This is a 6-month, hands-on role for someone who thrives at the intersection of research, data, and operations and wants to leave things working better than where they found them. This role is ideal for someone who loves sprinting on complex problems, is comfortable working across silos, and wants to make an outsized impact in just six months. This is a six month remote US role with a preference for candidates based on the East Coast.

Join the Enterprise Data and Analytics (EDA) team as a Sr. Data Platform Engineer, playing a central role in delivering data & GenAI solutions. You'll contribute to the Data Platform, develop GenAI Platform Capabilities, and drive technical decision-making. The technical day to day will primarily be within the Data Platform built using Snowflake, Dataiku & Github.

This role involves building a cohesive data organization that fosters collaboration and drives innovation across the entire company. The Senior Director of Data Engineering will drive the transformation of multiple teams and forge partnerships between the data organization and product engineering, while also enhancing the company’s competitive edge.