Together AI is building the Inference Platform that brings the most advanced generative AI models to the world. Our platform powers multi-tenant serverless workloads and dedicated endpoints, enabling developers, enterprises, and researchers to harness the latest LLMs, multimodal models, image, audio, video, and speech models at scale. If you get a thrill from optimizing latency down to the last millisecond, this is your playground. 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.