Member of Technical Staff - Workers AI Applied Research

Cloudflare, Inc.; Germany; Hybrid; EUR 166,000 - 229,000; Full time

Job summary

Cloudflare, Inc. is seeking an experienced ML Engineer to define how machine learning models run across its global network and productionize serving workflows.

You will work with systems engineers, product teams, hardware partners, and AI/ML engineers to bring models into production with low latency, reliability, and efficient resource use. You will focus on benchmarking, improving serving performance, validating quality, and building tooling that enables Cloudflare and its customers to ship AI

Qualifications

• 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.

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.

Skills

Python

PyTorch

TensorFlow

JAX

LLMs

Inference optimization

Quantization

Batching

Caching

Model deployment

GPUs

Tools

SGLang

vLLM

TensorRT-LLM

ONNX Runtime

Triton

llama.cpp

Job description

About Us

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 | New York, NY | San Francisco, CA or London, UK (Hybrid)

About the Role

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. You’ll work with systems engineers, product teams, hardware partners, and AI/ML engineers to bring models into production with low latency, strong reliability, and efficient resource use. This role combines applied ML, inference optimization, evaluation, and production engineering, with a focus on benchmarking models, improving serving performance, validating quality, and building tooling that helps Cloudflare and its customers ship AI applications at Internet scale.

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.
• Bonus Points: Experience contributing to open source ML tooling, model serving frameworks, or inference runtimes.

Compensation

Compensation may be adjusted depending on work location. For Bay Area based hires: Estimated annual salary of $194,000 - $266,000. For New York City, New Jersey, Washington, Washington DC, and California (excluding Bay Area) based hires: Estimated annual salary of $185,000 - $254,000. Equity…