Runpod is the AI Developer Cloud. More than one million developers, from indie researchers to teams running frontier models in production, use Runpod to experiment, train, fine-tune, deploy, and scale AI on one platform. We're a small, remote-first team.

We're looking for a ML Systems Engineer, Inference. You'll own LLM serving performance end to end. That means measuring it, understanding it, and improving it across models, hardware generations, and workloads.

This is a hands-on engineering role for someone who likes finding the real bottleneck and fixing it, then turning that fix into something that runs reliably in production. Define how we measure inference performance, including throughput, time to first token, inter-token latency, and cost per token, and build the tooling that makes those measurements rigorous and repeatable. Profile and diagnose performance problems across the serving stack, from scheduling and memory management down to kernels and interconnect.

Improve serving efficiency for large, state-of-the-art models on single-node and multi-node GPU deployments. Turn what you learn into production-ready runtimes, configurations, and defaults that customers benefit from automatically. Trace bottlenecks in the serving engine/runtime and implement fixes when configuration tuning is not enough. 5+ years of professional system engineering experience.





Strong software engineering skills in Python . You're comfortable working in large, performance-critical codebases. A solid understanding of what drives LLM inference performance: batching, memory, parallelism, and the trade-offs between latency and throughput.

Rigor in benchmarking and performance analysis, plus comfort with GPU profiling tools. The ability to explain your results clearly in writing and turn them into decisions.

Experience writing or tuning GPU kernels in CUDA or Triton. Contributions to inference or ML systems projects.

Experience with multi-node GPU systems and high-speed networking. Generous medical, dental & vision plans Most roles are remote work first with an inclusive, collaborative teams utilizing slack as the main form of internal communication 1,200 Home Office & Equipment Stipend-We set you up for success from day one with gear and support to create your idóneo workspace We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, protected veteran status, disability status, or any other characteristic protected by law. We welcome every qualified candidate eligible to work in the United States; however, we are currently unable to sponsor employment visas. #

📌 Remote Senior Ml Systems Engineer, Inference (Badajoz)
🏢 Runpod
📍 Badajoz