# Member of Technical Staff - Imagine Model

**Company**: xAI
**Location**: Palo Alto, CA; Seattle, WA
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $180,000 - $440,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q120599684

**Apply**: https://job-boards.greenhouse.io/xai/jobs/5051985007
**Canonical**: https://yubhub.co/jobs/job_8a3caae4-044

## Description

As a Member of Technical Staff on the Imagine Model Team, you will develop cutting-edge AI experiences beyond text, with a strong focus on enabling high-fidelity understanding and generation across image and video modalities. Responsibilities span data curation, modeling, training, inference serving, and product integration, covering both pretraining and post-training phases. You will collaborate closely with product teams to push model frontiers and deliver exceptional end-to-end user experiences.

Key responsibilities include creating and driving engineering agendas to advance multimodal capabilities, improving data quality through annotation, filtering, augmentation, synthetic generation, captioning, and in-depth data studies, designing evaluation frameworks, metrics, benchmarks, evals, and reward models tailored to image/video/audio quality and coherence, implementing efficient algorithms for state-of-the-art model performance, and developing scalable data collection and processing pipelines for multimodal (primarily image/video-focused) datasets.

The ideal candidate will have a track record in leading studies that significantly improve neural network capabilities and performance through better data or modeling, experience in data-driven experiment designs, systematic analysis, and iterative model debugging, experience developing or working with large-scale distributed machine learning systems, and ability to deliver optimal end-to-end user experiences.

## Skills

### Required
- data curation
- modeling
- training
- inference serving
- product integration
- large-scale distributed machine learning systems

### Nice to have
- SFT
- RL
- evals
- human/synthetic data collection
- agentic systems
- Python
- JAX/XLA
- PyTorch
- Rust/C++
- Spark
- Ray