ML Infrastructure Engineer

xAI is seeking an ML Infrastructure Engineer to build and optimize the high-performance ML platform powering recommendations on X. You will design GPU compute infrastructure, develop data pipelines, and collaborate with ML teams to productionize models. The role involves working across the full stack to ensure scalability and efficiency of large-scale ML systems.

• Designing, building, and scaling GPU compute infrastructure, training frameworks, and experimentation tools
• Developing data pipelines and integrating large-scale data, training, and inference systems
• Collaborating with ML teams to productionize models and ensure seamless integration across the stack
• Ensuring scalability, reliability, and efficiency of large-scale machine learning systems
• Working across the full stack to solve complex problems independently
• Mentoring junior engineers and contributing to team growth

• Bachelor, Master, or PhD in computer science, machine learning, or equivalent experience
• 2+ years industry experience with high-traffic/large-scale production environments, distributed systems, GPU infrastructure, or deep learning
• 2+ years experience with ML platforms, training infrastructure, or collaboration with modeling engineers
• Strong proficiency in Python and experience with compiled languages such as C++ or Rust