# Senior Machine Learning Engineer **Company**: Cloudflare **Location**: Austin, TX **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Category**: Engineering **Industry**: Technology **Apply**: https://job-boards.greenhouse.io/cloudflare/jobs/8043974?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_5f67930c-642 ## Description At Cloudflare, we're on a mission to help build a better Internet. You'll help define how machine learning models run across Cloudflare's global network, from frontier open LLMs and real-time voice models to customer-deployed models served on heterogeneous GPUs and next-generation accelerators. ## Responsibilities - Develop, optimize, and productionize machine learning models for Cloudflare's serverless inference platform, with a focus on performance, reliability, and model quality. - Build benchmarking and evaluation frameworks to measure latency, throughput, cost efficiency, and model behavior across LLMs, speech, vision, and other model families. - Improve inference performance through quantization, batching, caching, model compilation, runtime tuning, and accelerator-aware optimization. - Partner with systems engineers to integrate models into Cloudflare's distributed inference infrastructure across a heterogeneous fleet of GPUs and next-generation accelerators. - Drive improvements to model deployment workflows, including validation, rollout safety, observability, regression testing, and operational readiness. - Collaborate with product and engineering teams to translate customer requirements into scalable ML capabilities for Workers AI. - Mentor engineers, contribute to technical direction, and raise the quality bar for production ML engineering practices across the team. ## Desirable Skills, Knowledge, and Experience - Experience building, optimizing, and operating machine learning models in production environments. - Strong proficiency with Python and modern ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent. - Hands-on experience with inference optimization techniques for large-scale models, including quantization, batching, caching, compilation, and serving runtime tuning. - Experience with large-scale inference serving frameworks or runtimes such as SGLang, vLLM, TensorRT-LLM, ONNX Runtime, Triton, llama.cpp, or similar. - Familiarity with LLMs, speech models, vision models, embeddings, multimodal models, retrieval-augmented generation, or other modern deep learning architectures. - Experience optimizing models for GPUs or specialized accelerators. - Strong understanding of production ML concerns, including evaluation, monitoring, model regressions, rollout safety, and reliability. - Ability to work across ML and systems boundaries, including familiarity with distributed systems, networking, or serverless platforms. - Track record of leading complex technical projects and mentoring other engineers. ## Skills ### Required - Python - PyTorch - TensorFlow - JAX - machine learning - inference optimization - large-scale models - distributed systems - serverless platforms ### Nice to have - experience with open source ML tooling - model serving frameworks - inference runtimes --- Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/cloudflare/jobs/8043974?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)