Where You Come InThis is a rare opportunity to build the foundational infrastructure that powers our large-scale multimodal models. We believe that reliable, high-performance infrastructure is the single biggest differentiating factor between success and failure in achieving our mission. You will be a foundational member of the team, designing the critical systems that allow us to train and serve next-generation AI to millions of users.
What You'll DoThis is a 0-to-1 opportunity, not a maintenance role. You will have massive ownership to:
- Architect end-to-end model serving pipelines and integrate new model architectures from our research team into our core, high-throughput inference engine.
- Build robust and sophisticated scheduling systems to manage jobs based on cluster availability and user priority, ensuring we optimally leverage thousands of expensive GPU resources.
- Design and implement dynamic, traffic-based systems for hotswapping models on our GPU workers to maximize fleet efficiency and meet product SLOs.
- Own the end-to-end CI/CD pipelines, including creating a resilient artifact store to manage all model checkpoints across multiple versions and providers.
- Develop and maintain user-friendly APIs and interaction patterns that empower our product and research teams to ship groundbreaking features at high velocity.
- Manage and optimize our complex inference workloads at scale, operating across multiple clusters and hardware providers.
Who You AreWe are looking for a world-class builder who has a proven history of creating and managing large-scale, high-performance systems. You are a non-negotiable fit if you have:
- 5+ years of professional engineering experience with deep, hands-on proficiency in Python and complex distributed systems architecture.
- Extensive, practical experience building and managing systems at scale, specifically with queues, scheduling, traffic-control, and fleet management.
- Deep expertise in our core infrastructure stack: Linux, Docker, and Kubernetes.
- Strong experience with Redis, S3-compatible storage, and public cloud platforms (AWS).
What Sets You Apart (Bonus Points)You'll stand out as an exceptional candidate if you also bring:
- Experience with high-performance, large-scale ML systems (managing >100 GPUs).
- Deep familiarity with PyTorch and CUDA.
- Experience with modern networking stacks, including RDMA (RoCE, Infiniband, NVLink).
- Familiarity with FFmpeg and multimedia processing pipelines.
CompensationThe base pay range for this role is $187,500 - $395,000 per year.
