AI Frontier · AI lab
Currently tracking 76 active AI roles, down 16% versus the prior 4 weeks. Primary focus: Data · Engineering. Salary range $148k–$600k (avg $306k).
| Title | Stage | AI score |
|---|---|---|
| Member of Technical Staff - X Search The X Search team is responsible for building and operating the core search engine that powers discovery on X. This role involves building and operating large-scale search engines and infrastructure, training state-of-the-art ML ranking models, and integrating Grok's reasoning capabilities into search systems and products. The role requires experience with vector databases, search indices, and production ML systems. | ShipAgent | 8 |
| Member of Technical Staff - Imagine Product This role focuses on building and scaling systems for AI-driven media experiences, specifically for Grok users. It involves designing and implementing scalable infrastructure for real-time multi-modal interactions, processing various media types, and collaborating with research and product teams to deliver consumer-facing features. The role emphasizes full-cycle development from design to deployment and monitoring, aiming to reach hundreds of millions of users. | ShipServe | 8 |
| Member of Technical Staff - Ads This role involves integrating Grok models into a large-scale Ads Platform, covering aspects like candidate selection, ranking, auction, optimization, and creative generation. The engineer will own and operate these revenue-driving systems. | Ship | 7 |
| Member of Technical Staff - Recommendation Systems Seeking exceptional Applied engineers to work on a high-priority project with ~600 million monthly users, focusing on recommendation systems, ranking algorithms, and search technologies. Responsibilities include designing and architecting recommendation algorithms, leveraging AI stacks, writing data pipelines and training jobs, iterating through user feedback and experimentation, and ensuring scalability and efficiency of ML systems. Requires knowledge of data infrastructure (Kafka, Clickhouse, Spark), experience implementing recommender systems/deep learning at industrial scale, and proficiency in DL frameworks (JAX, PyTorch). CUDA kernel experience is a plus. | Ship | 7 |