Senior Software Engineer

Responsibilities

• Design and build across the full stack from public training APIs and SDKs through the control plane to the GPU data plane
• Scale distributed systems for serverless GPU compute including multi-tenant scheduling and capacity-aware routing
• Drive end-to-end performance for training, inference, and RL loops to ensure high GPU saturation
• Productionize research building blocks by partnering with Snowflake Research to turn SOTA techniques into reliable components

Requirements

• 5+ years of experience building and shipping production ML systems
• Strong foundation in distributed systems and infrastructure design
• Experience operating scalable, fault-tolerant services on Kubernetes
• Familiarity with GPU and LLM infrastructure such as PyTorch, DeepSpeed/FSDP, Ray, CUDA/NCCL, or vLLM
• Ability to debug across data, infrastructure, and GPU layers
• BS in Computer Science or a related field

Preferred Qualifications

• MS or PhD in a related field
• Hands-on LLM post-training or modeling experience

About the Company

Snowflake's ML Platform team enables customers to run demanding ML/AI workloads inside Snowflake. Cortex Training is an LLM post-training platform that turns GPU capacity into a simple, composable service for adapting foundation models to business problems.