Baseten
Software Engineer - Baseten Inference Stack
About this role
Join Baseten's Inference Stack team to build the distributed runtime powering large-scale LLM inference. You'll work across the full stack—from developer tools to Kubernetes orchestration—enabling AI companies to deploy cutting-edge models with industry-leading performance and reliability.
What you'll do
- Develop infrastructure and orchestration systems for distributed LLM inference at scale
- Build platform capabilities for routing, autoscaling, scheduling, observability, and runtime management
- Work across the stack from customer-facing features to low-level infrastructure components
- Collaborate with Model Performance engineers to make inference optimizations accessible and configurable
- Debug complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads
- Own end-to-end projects from architecture through deployment and iteration based on customer feedback
What they're looking for
- Distributed systems and backend infrastructure
- Platform engineering and production systems
- Kubernetes and container orchestration
- Debugging across multiple stack layers
- Developer experience design
- GPU workload management
- Willingness to learn new languages and frameworks
- Strong communication and collaboration
Benefits
- Work on mission-critical inference powering leading AI companies like Cursor and Notion
- Recently raised $1.5B Series F with top-tier investors
- Located in San Francisco
- Opportunity to own systems in production
- Cross-functional collaboration with Model Performance teams
- Impact on frontier AI infrastructure
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Baseten
Baseten builds an AI inference platform that enables companies to deploy and manage machine learning models in production at scale. The company is hiring software engineers, infrastructure specialists, and product engineers to develop observability systems, frontend experiences, reliability infrastructure, developer tools, and enterprise deployment solutions.
- Website
- baseten.com
Likely interview questions
- Tell us about a time you debugged a complex production issue spanning multiple layers of the stack. What was your approach and what did you learn?
- Describe your experience building or operating distributed systems where reliability, latency, and scale were critical. What were the biggest challenges?