ML Infrastructure Engineer

SpaceXAI; United States; On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical, vision, dental

401(k) retirement plan

Disability insurance

Job summary

SpaceXAI is hiring an ML Infrastructure Engineer to design and scale a high-performance ML platform powering recommendations. You will own GPU compute infrastructure, training frameworks, and experimentation tools to accelerate ML research and production throughput.

You will collaborate with ML teams to productionize models, ensure reliability, and optimize the stack from data ingestion to inference. The role includes mentoring junior engineers and shaping the future of our infrastructure.

Qualifications

• Bachelors/Masters/PhD in CS or quantitative field or equivalent experience (BSc/BEng not required).
• 2+ years in high-traffic or large-scale production environments.
• 2+ years with ML platforms, training infra, or modeling collaboration.
• Strong Python, plus C or Rust is a plus.

Responsibilities

• Design, build, and scale GPU compute infrastructure and training frameworks.
• Develop data pipelines for large-scale data, training, and inference.
• Collaborate with ML teams to productionize models across the stack.
• Ensure scalability, reliability, and efficiency of ML systems.
• Work across the full stack to solve problems independently.
• Mentor junior engineers and contribute to team growth.

Skills

Python programming

Distributed systems

ML platforms

GPU infrastructure

Strong communication

Education

Bachelor/Master/PhD in CS or related field

Tools

CUDA toolkits

NVIDIA drivers

Slurm

Puppet/Ansible

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.
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