AI Infrastructure Engineer

xAI is on a mission to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. As an organization, we maintain a flat structure where all employees are hands-on contributors to our mission. Our small, highly motivated team values engineering excellence and intellectual curiosity.

The post-training team plays a crucial role in transforming pre-trained models into steerable, versatile systems capable of addressing real-world challenges. As an AI Infrastructure Engineer, you'll be at the forefront of developing and optimizing frameworks for large-scale machine learning tasks, with a particular focus on reinforcement learning and agent systems.

Your role will involve building high-performance, scalable software that supports cutting-edge AI research. You'll be working on creating efficient training and evaluation frameworks for model fine-tuning, developing large-scale agent simulation systems, and constructing flexible bulk inference frameworks for synthetic data generation.

We're looking for experts in distributed machine learning systems who have deep knowledge of GPUs, Kubernetes, and JAX/PyTorch. You'll be working with cutting-edge technologies including Python, JAX, Rust, and CUDA & NCCL. The role offers an opportunity to push the boundaries of AI capabilities through increased data and computational resources.

Located in the vibrant Bay Area, you'll be part of a team that values strong communication skills and the ability to share knowledge effectively. The position offers competitive compensation ranging from $180,000 to $440,000 USD annually. Our interview process is thorough but efficient, designed to evaluate both technical expertise and cultural fit through coding assessments, technical sessions, and team presentations.

Join us if you're passionate about advancing AI technology, thrive in a fast-paced environment, and want to be part of a team that's pushing the boundaries of what's possible in artificial intelligence.