Senior Machine Learning Engineer

Навыки

• CUDA / ONNX / TensorRT
• Распределённые системы
• DNS / DHCP
• LLM
• Инференс LLM
• Machine Learning
• Мониторинг и observability

О компании и продукте

• At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.
• At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.
• Available Locations: Austin, TX

Задачи

• 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

Требования

• Hands-on experience with inference optimization techniques for large-scale models, including quantization, batching, caching, compilation, and serving runtime tuning
• Ability to work across ML and systems boundaries, including familiarity with distributed systems, networking, or serverless platforms

Будет плюсом

• 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
• 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
• Track record of leading complex technical projects and mentoring other engineers
• Experience contributing to open source ML tooling, model serving frameworks, or inference runtimes
• What Makes Cloudflare Special?
• We’re not just a highly ambitious, large-scale technology company
• We’re a highly ambitious, large-scale technology company with a soul
• Fundamental to our mission to help build a better Internet is protecting the free and open Internet
• Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost
• Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration
• Since the project, we've provided services to more than 425 local government election websites in 33 states
• 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver
• This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released
• Here’s the deal - we don’t store client IP addresses never, ever
• We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers
• Sound like something you’d like to be a part of? We’d love to hear from you!
• Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs
• More details about this will be available at that stage of the interview process
• This position may require access to information protected under U.S. export control laws, including the U.S

Паспорт вакансии

История публикации

Откуда что взялось

Отмечено то, что вывели мы. Без пометки — значение назвал работодатель.

Почему на этом месте в выдаче

Порядок выдачи объявлен контрактом: свежесть решает между днями, полнота и зарплата — внутри дня.