ML Infrastructure Engineer
$180k - $440k • Palo Alto, CA
Posted 4d ago
About the job
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
- Design, build, and scale GPU compute infrastructure, training frameworks, and experimentation tools.
- Develop data pipelines and integrate large-scale data, training, and inference systems.
- Collaborate with ML teams to productionize models and ensure seamless integration.
- Ensure scalability, reliability, and efficiency of large-scale machine learning systems.
- Solve complex problems across the full stack independently.
- Mentor junior engineers and contribute to team growth.
Requirements
- Bachelor's, Master's, Post-graduate, or PhD in computer science, machine learning, or a related quantitative discipline, or equivalent work experience.
- 2+ years of industry experience with high traffic or large-scale production environments, distributed systems, GPU infrastructure, and/or deep learning applications.
- 2+ years of experience with ML platforms, training infrastructure, or close collaboration with modeling engineers and data scientists.
- Strong proficiency in Python and experience with compiled languages like C++ or Rust.
- 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.
- Comfort with Linux systems and orchestration tools.
- Experience with job schedulers (e.g., Slurm), configuration management (Puppet/Ansible), or related infrastructure tooling.
Benefits
- Equity
- Comprehensive medical, vision, and dental coverage
- Access to a 401(k) retirement plan
- Short & long-term disability insurance
- Life insurance
- Various other discounts and perks