Senior Backend Engineer (Inference Platform)

• You’ll work hands-on with tens of thousands of GPUs (H100s, H200s, GB200s, and beyond), figuring out how to fully utilize every FLOP and every gigabyte of memory
• You’ll collaborate directly with research teams to bring frontier models into production, making breakthroughs usable in the real world. Our team also works closely with the open source community, contributing to and leveraging projects like SGLang, vLLM, and NVIDIA Dynamo to push the boundaries of inference performance and efficiency
• Build and optimize global and local request routing, ensuring low-latency load balancing across data centers and model engine pods
• Develop auto-scaling systems to dynamically allocate resources and meet strict SLOs across dozens of data centers
• Design systems for multi-tenant traffic shaping, tuning both resource allocation and request handling — including smart rate limiting and regulation — to ensure fairness and consistent experience across all users
• Engineer trade-offs between latency and throughput to serve diverse workloads efficiently
• Optimize prefix caching to reduce model compute and speed up responses
• Collaborate with ML researchers to bring new model architectures into production at scale
• Continuously profile and analyze system-level performance to identify bottlenecks and implement optimizations

Benefits

• Competitive health insurance plans
• Pre-tax flexible spending accounts
• Dental and vision insurance
• Income protection & retirement
• Mental health support and services
• AD&D insurance
• 401(k) plan
• Life insurance
• STD & LTD insurance
• Monthly commuting stipend + pre-tax bene
• Flexible time off policy
• Monthly team lunches
• Team-driven celebrations and events

• If you get a thrill from optimizing latency down to the last millisecond, this is your playground
• Experience with Kubernetes or container orchestration is a strong plus
• 5+ years of demonstrated experience building large-scale, fault-tolerant, distributed systems and API microservices
• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience
• Strong background in designing, analyzing, and improving efficiency, scalability, and stability of complex systems
• Knowledge of modern LLMs and generative models and how they are served in production is a plus
• Expert-level programming in one or more of: Rust, Go, Python, or TypeScript
• Familiarity with GPU software stacks (CUDA, Triton, NCCL) and HPC technologies (InfiniBand, NVLink, MPI) is a plus
• Excellent understanding of low-level OS concepts: multi-threading, memory management, networking, and storage performance
• Experience working with the open source ecosystem around inference is highly valuable; familiarity with SGLang, vLLM, or NVIDIA Dynamo will be especially handy