ML Infrastructure Engineer

Pantera Capital; Palo Alto (CA); On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Comprehensive medical, vision, and/or

Dental coverage

401(k) retirement plan

Short & long-term disability insurance

Life insurance

Employee discounts

Job summary

SpaceXAI is seeking an ML Infrastructure Engineer to build and optimize a high-performance ML platform that powers recommendations on X. You will design, deploy, and scale GPU compute infrastructure, training frameworks, and data pipelines to support rapid ML experimentation.

The role requires deep experience with Python and compiled languages (C++/Rust), plus collaboration with ML squads to productionize models across the stack.

Qualifications

• Bachelor, Master, Post-graduate or PhD in CS, ML, or quantitative field; or equivalent work experience.
• 2+ years in high-traffic or large-scale production environments, distributed systems, GPU infrastructure, or DL applications.
• 2+ years experience with ML platforms, training infrastructure, or collaboration with modeling engineers and data scientists.
• Strong proficiency with Python and compiled languages such as C++ or Rust.

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
• 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 the growth of the team

Skills

Python

C++

Rust

Distributed systems

GPU infrastructure

ML frameworks

Linux

Networking

Education

Bachelor/Master/PhD in CS/ML

Tools

Slurm

Puppet/Ansible

CUDA toolkit

NVIDIA drivers

Job description

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. 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.

ABOUT THE ROLE:

As an ML Infrastructure Engineer, you will play a pivotal role in building and optimizing the reliable, high-performance ML platform that powers recommendations on X. 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
• 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 the growth of the team

BASIC QUALIFICATIONS:

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

PREFERRED SKILLS AND EXPERIENCE:

• 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

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

SpaceXAI is an equal opportunity employer.

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