Software Engineer, Inference
Sierra · San Francisco, CA
About this role
## About Sierra Sierra is the leading platform for customer-facing AI agents, working with major brands including **The GAP, Rocket Mortgage, SoFi, Sutter Health,** and **SoftBank** to transform how they serve customers and grow their businesses. We’re primarily an **in-person** company based in **San Francisco**, with growing offices across **North America, Europe, and Asia**. Our values guide our culture and the way we work: **Trust, Customer Obsession, Craftsmanship, Intensity,** and a commitment to balancing **Family**. ## About the Role — Software Engineer, Inference Sierra’s AI agents rely on foundation models to reason and act in real time. The **Inference** team builds the systems that make those models **fast, reliable, and efficient at scale**. As a Software Engineer on Inference, you’ll help define Sierra’s **inference architecture** across both **self-hosted models** and **third-party inference providers**. You’ll work on systems for **serving and routing inference**, **managing capacity and quota**, and optimizing for **latency, reliability, and cost**. This is a **systems-first** role at the intersection of **distributed infrastructure and AI**. You don’t need to be an ML researcher—we’re looking for engineers who love complex systems problems and want to apply that expertise to fast-moving AI infrastructure. ## What You’ll Do - **Partner with frontier labs and providers** to source capacity and inference infrastructure. - **Shape Sierra’s inference architecture** by designing how inference traffic flows across models, infrastructure, and providers (including new serving/proxy layers as Sierra scales). - **Build for low latency and high reliability**, including routing, failover, capacity management, and quota. - **Build and operate self-hosted inference** on GPU infrastructure (containers, inference engines, and compute capacity management). - **Optimize inference performance** with the Applied Research team (e.g., speculative decoding and serving-engine optimizations). - **Build across a hybrid inference stack** across Sierra-managed infrastructure and leading inference platforms. - **Push the serving stack forward** by working with inference providers to tune engines and infrastructure for Sierra’s workloads. - **Support the broader model lifecycle** by contributing to infrastructure that enables post-training.
Listing freshness
CronJobs last confirmed this listing 2d ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.