ML Infrastructure Engineer

USD 180,000-440,000 per year

MIDDLE

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Ansible @ 3 CUDA @ 3 Data Pipelines Deep Learning @ 3 Distributed Systems @ 3 Experimentation GPU @ 3 JAX @ 2 Linux @ 3 Machine Learning @ 3 Mentoring Networking @ 3 Puppet @ 3 PyTorch @ 2 Python @ 6 Rust @ 6 Slurm @ 3

Details

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 SpaceXAI’s most demanding training and inference workloads.

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

Requirements

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.