Software Engineer, Distributed Systems

Responsibilities

• Take ownership of Rust/Python systems powering AI inference and large-scale GPU computing platform
• Design for 100x growth in workloads and GPU capacity with reliable, low-latency execution
• Use AI aggressively to accelerate development and automate operations, alerting, and recovery
• Specialize in areas such as request routing, app deployment, autoscaling, worker orchestration, GPU fleet management, global file storage, or global IP backbone

Requirements

• 3+ years building and operating large-scale production systems
• Strong Rust and/or Python skills
• Strong systems fundamentals (distributed coordination, scheduling, fault tolerance, Linux, networking, storage, or capacity management)
• Experience building and using observability to drive performance and reliability decisions
• Clear communication and sound technical judgment

Preferred Qualifications

• Experience with multi-tenant compute platforms, AI inference, or training infrastructure
• High-performance systems programming (async runtimes, zero-copy, memory-safe concurrency)
• Linux systems engineering and fleet automation
• Experience with distributed filesystems like JuiceFS and Lustre
• Experience with Nvidia/AMD GPU infrastructure (DCGM, NVLink, RDMA, InfiniBand/RoCEv2)
• Experience with global networking and routing (BGP, ECMP, tunnels, eBPF, Geneve)

About the Company

fal is the generative media ecosystem powering the next generation of AI products, providing high-performance inference, orchestration, and observability on a unified platform.