🤖 AI Infrastructure Engineer - Founding Team
📍 On-site, San Francisco, CA
💵 $200k - $300k + Equity
About the Company:
Our client is pioneering AI infrastructure with a distributed platform that leverages global GPU capacity to power high-performance machine learning inference. Backed by over $10 million from leading investors, they are reimagining how AI applications scale, driven by a small team of seasoned engineers tackling some of the toughest infrastructure challenges in the field.
The Role:
As a AI Infrastructure Engineer, you will be instrumental in designing and building robust systems for large-scale, high-throughput ML inference. This role demands expertise in distributed systems and experience with infrastructure optimized for low-latency inference. You’ll join an elite team in San Francisco, driving solutions that enable millions of daily inference requests and redefining resource allocation.
This is a full-time, on-site position in San Francisco.
What You’ll Do:
💻 Build and optimize fault-tolerant systems to handle large-scale ML inference.
🚀 Design scalable, real-time APIs and distributed systems for high-volume, low-latency workloads.
📈 Develop Monitoring & Diagnostics Tools to ensure system health, logging, and real-time performance tracking.
⚙️ Work closely with a small, expert team to continuously improve platform capabilities with the latest in GPU and ML tooling.
🔍 Conduct Architecture & Code Reviews, ensuring high standards and best practices.
What We’re Looking For:
- Extensive experience in AI infrastructure and distributed systems development.
- Strong programming skills in Typescript, Python, and one of either Go, Rust, or C++.
- Proficiency with orchestration frameworks like Kubernetes or Nomad.
- Experience with GPU programming and AI inference engines (e.g., vLLM, TensorRT) is a plus.
- Prior experience in fast-paced startup environments, particularly in early-stage teams.
If you’re ready to shape the future of AI infrastructure in a high-impact role, apply today! 🚀
