xAI

xAI

ML Infrastructure Engineer

Palo Alto, California, United States

Sponsorship not specified$180k-$440kDetected 12 hours ago
PythonRustC++Distributed SystemsFull-Stack DevelopmentAnsibleLinuxMachine LearningDeep LearningPyTorchData EngineeringA/B TestingLeadershipCommunicationCollaborationMentoring

About the role

  • We're looking for exceptional engineers who are passionate about our mission and have a strong desire to make a meaningful impact.

Responsibilities

  • Designing, building, and scaling GPU compute infrastructure, training frameworks, and experimentation tools to enable rapid iteration on ML hypotheses
  • Developing data pipelines and integrating large-scale data, training, and inference systems

Requirements

  • 2+ years experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists
  • Strong proficiency with Python and experience with compiled languages such as C++ or Rust

Skills

  • Deep familiarity with modern ML frameworks such as JAX or PyTorch
  • Low-level understanding of compute systems, including distributed storage, NVIDIA drivers, CUDA toolkits, and networking
  • Comfortable with Linux systems and orchestration tools
  • Experience with job schedulers (e.g., Slurm), configuration management (Puppet/Ansible), or related infrastructure tooling
  • This organization is for individuals who appreciate challenging themselves and thrive on curiosity.
  • All employees are expected to be hands-on and to contribute directly to the company's mission.
  • Work ethic and strong prioritization skills are important.
  • All employees are expected to have strong communication skills.
  • They should be able to concisely and accurately share knowledge with their teammates.

Compensation

  • $180,000 - $440,000 USD

Benefits

  • Ensuring scalability, reliability, and efficiency of large-scale machine learning systems
  • Bachelor, Master, Post-graduate or PhD in computer science, machine learning, or other quantitative discipline
  • 2+ years of industry experience working with high traffic or large-scale production environments, distributed systems, GPU infrastructure, and/or deep learning applications

Equal opportunity

  • equal opportunity employer.
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This listing is sourced directly from xAI's careers page and normalized into a canonical job model.