Software Engineer, Distributed Systems

fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products.

As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on.

You are an experienced software engineer who thrives on building large-scale computing platforms. You have deep expertise in large scale distributed systems that deal with high complexity, a lot of traffic and data. You know how to achieve reliability and scale with minimum operational load.

• →Build our core Python/Rust platform: request routing, AI workload orchestration, scheduling, GPU autoscaling, large scale file storage, queueing, etc
• →Produce forward designs for platform evolution as we scale to 100x current traffic and need to provide low latency across the world
• →Leverage AI to an extreme level to automate the mundane parts of building complex but reliable systems
• →Profile and tune low level CPU and memory performance

• 3+ years experience building distributed compute and orchestration platforms in Python or Rust
• Strong understanding of distributed systems fundamentals: consensus, scheduling, fault tolerance, capacity planning
• Deep understanding of computational complexity and memory allocation
• Track record of designing systems that scale under real production load
• Experience building and using observability to drive performance and reliability decisions
• Excellent communication and ability to drive technical decisions across teams
• Self-starter who executes quickly, takes ownership, and constantly seeks improvement

• Experience with AI/ML inference or training infrastructure
• Experience with high-performance systems programming (async runtimes, zero-copy, memory-safe concurrency)
• Background in building multi-tenant compute platforms
• Understanding of networking fundamentals and performance characteristics
• Familiarity with GPU workload characteristics and scheduling constraints

• San Francisco, CA (willing to consider remote for Senior and Staff levels)