AI Engineer & Researcher - Pre-training Scaling, Data, and Eval
Description For AI Engineer & Researcher - Pre-training Scaling, Data, and Eval
xAI, a cutting-edge AI research company, is seeking an AI Engineer & Researcher specializing in pre-training scaling, data, and evaluation. The role is based in the Bay Area (San Francisco and Palo Alto) and offers a competitive salary range of $180,000 - $440,000 USD.
The company operates with a flat organizational structure where all employees are hands-on contributors to the mission of creating AI systems that can accurately understand the universe. The team is small, highly motivated, and focused on engineering excellence, making it an ideal environment for curious individuals who thrive on challenges.
The role involves working with state-of-the-art AI technologies, including training trillion-parameter neural networks and implementing cutting-edge methods from deep learning literature. The tech stack includes Python, JAX and XLA, Rust/C++, and Spark. The successful candidate will be responsible for innovating new ideas for pretraining and scaling paradigms, while also improving data quality across different modalities.
The ideal candidate should possess strong engineering skills, expertise in ML and large model scaling, and familiarity with distributed training and multi-GPU neural network optimization. They should also have experience with AI training data preparation and be skilled at organizing data across multiple clouds and modalities.
The interview process is thorough but efficient, typically completed within one week, consisting of a phone screening followed by four technical interviews including coding assessment, systems hands-on, project deep-dive, and team meet-and-greet. The company values strong communication skills and the ability to share knowledge effectively with teammates.
Responsibilities For AI Engineer & Researcher - Pre-training Scaling, Data, and Eval
- Training trillion parameter neural networks at scale, as well as a variety of smaller specialized models
- Rapidly implementing the latest state-of-the-art methods from the deep learning literature
- Innovating new ideas for pretraining and new scaling paradigm
- Improving pretraining data quality at scale across different modalities
Requirements For AI Engineer & Researcher - Pre-training Scaling, Data, and Eval
- Strong engineering skills with passion to improve different aspects of data and model
- Expert in ML and large model scaling, familiar with all kinds of scaling laws
- Familiar with distributed training, multi-GPU neural network training and experience on optimizing ML training efficiency
- Familiar with state-of-the-art techniques for preparing AI training data
- Good at organizing and meticulously bookkeeping data across multiple clouds, of multiple modalities, and from many sources
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