ML Infrastructure Engineer

Socket.dev; Palo Alto (CA); On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical coverage

Vision coverage

Dental coverage

401(k)

Short/Long disability insurance

Life insurance

Discounts

Job summary

SpaceXAI seeks an ML Infrastructure Engineer to design and scale a high-performance ML platform powering recommendations. You will build GPU compute infra, data pipelines, and tooling to accelerate experimentation and productionization of models.

You will collaborate with ML teams to integrate models across the stack, ensure reliability, and mentor junior engineers while tackling complex systemic challenges.

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 with large-scale production environments, distributed systems, GPU infra, and/or deep learning applications
• 2+ years experience with ML platforms, training infrastructure, or collaboration with modeling engineers and data scientists
• Strong proficiency with Python and experience with 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 platforms

Linux

Slurm

Education

Bachelor/Master/PhD in CS/ML

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

• equity
• comprehensive medical, vision, and dental coverage
• 401(k) retirement plan
• short term disability insurance
• long term disability insurance
• life insurance
• various other discounts and perks

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