ML Infra Engineer — Scale GPU ML Platform & Equity

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 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.