Cloudflare

2 weeks ago

Senior Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Define how machine learning models run across a global serverless inference platform, from frontier LLMs and speech/vision models to customer-deployed inference on heterogeneous GPUs and accelerators. Build benchmarking and evaluation frameworks, improve latency/throughput/cost via quantization and runtime tuning, and integrate models into distributed infrastructure. Drive safer model deployment workflows for low-latency, reliable quality at Internet scale, while mentoring engineers and raising production ML standards.

Location: Austin

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Develop, optimize, and productionize machine learning models for a serverless inference platform, focusing 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 via quantization, batching, caching, model compilation, runtime tuning, and accelerator-aware optimization.
•Partner with systems engineers to integrate models into distributed inference infrastructure across heterogeneous GPUs and next-generation accelerators.
•Drive deployment workflow improvements including validation, rollout safety, observability, regression testing, and operational readiness, while mentoring engineers.

Key Requirements

•Experience building, optimizing, and operating machine learning models in production environments.
•Strong proficiency with Python and modern ML frameworks such as PyTorch, TensorFlow, or JAX (or equivalent).
•Hands-on experience with inference optimization for large-scale models, including quantization, batching, caching, compilation, and runtime tuning.
•Experience with large-scale inference serving frameworks or runtimes such as vLLM, TensorRT-LLM, ONNX Runtime, Triton, SGLang, or llama.cpp (or similar).
•Familiarity with modern deep learning architectures including LLMs, speech, vision, embeddings, multimodal models, or retrieval-augmented generation.

Experience:Open sourceLLMs

Skills:MentorshipTechnical leadershipCross-functional collaboration

Languages:English

Tech Stack:PythonPyTorchTensorFlowJAXSGLangVLLMTensorRT-LLMONNX RuntimeTritonLlama.cppQuantizationBatchingCachingModel compilationRuntime tuningGPUsAcceleratorsWorkers AI

Company Brief

Cloudflare

Provides a global network and cloud platform that delivers security, performance, and reliability services for web applications, APIs, and Internet properties, including CDN, DDoS protection, DNS, and zero-trust security solutions.

Industry: Cybersecurity

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2009

Website LinkedIn

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Cloudflare

2 weeks ago

Senior Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Austin

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Develop, optimize, and productionize machine learning models for a serverless inference platform, focusing 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 via quantization, batching, caching, model compilation, runtime tuning, and accelerator-aware optimization.
•Partner with systems engineers to integrate models into distributed inference infrastructure across heterogeneous GPUs and next-generation accelerators.
•Drive deployment workflow improvements including validation, rollout safety, observability, regression testing, and operational readiness, while mentoring engineers.

Key Requirements

•Experience building, optimizing, and operating machine learning models in production environments.
•Strong proficiency with Python and modern ML frameworks such as PyTorch, TensorFlow, or JAX (or equivalent).
•Hands-on experience with inference optimization for large-scale models, including quantization, batching, caching, compilation, and runtime tuning.
•Experience with large-scale inference serving frameworks or runtimes such as vLLM, TensorRT-LLM, ONNX Runtime, Triton, SGLang, or llama.cpp (or similar).
•Familiarity with modern deep learning architectures including LLMs, speech, vision, embeddings, multimodal models, or retrieval-augmented generation.

Experience:Open sourceLLMs

Skills:MentorshipTechnical leadershipCross-functional collaboration

Languages:English

Tech Stack:PythonPyTorchTensorFlowJAXSGLangVLLMTensorRT-LLMONNX RuntimeTritonLlama.cppQuantizationBatchingCachingModel compilationRuntime tuningGPUsAcceleratorsWorkers AI

Company Brief

Cloudflare

Industry: Cybersecurity

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2009

Website LinkedIn