Machine Learning Engineer

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 - Bengaluru, India About the Role The Data Intelligence & Analytics organization builds the core data platform and internal products that power decision-making across the company. We design and operate large-scale data systems, own the company’s data lake, ingestion infrastructure, and platform tooling, and develop end-to-end applications that transform complex datasets into fast, reliable, business-critical products used daily by go-to-market, product, and engineering teams. Our work sits at the intersection of data platforms, distributed systems, and product development, giving engineers the opportunity to own meaningful problems across the stack and build systems that truly run the business. We are looking for an experienced Machine Learning Engineer to join our Bengaluru team and help scale the next generation of our AI/ML models. In this role, you will build and operate the pipelines behind AI-driven applications, Agents, Chatbots that power teams across the company, including go-to-market, engineering, and product. Because the products we build are initiated and owned by the team, you will be involved end-to-end — from shaping requirements and designing systems to implementation, deployment, and long-term ownership. You will focus on building scalable, reliable services and application backends, partnering closely with data and full-stack engineers to deliver new features and operate the pipelines and platforms behind our products. Our stack spans multiple languages and technologies, including Python, React, and TypeScript, and continues to evolve. Many of our applications also incorporate strong AI components, giving you opportunities to work with modern AI infrastructure and tools such as vector databases, MCP-based services, and Workers AI. Responsibilities - Deploy, manage & support ML Applications & Services on Kubernetes - Understand MLOps landscape i.e tooling, tech stack, source systems etc. and work on introducing new tools and solutions for ML & AI initiatives. - Partner and align with Data Scientists, Data Engineers and internal teams to deliver ML solutions in a globally distributed environment. - Lead development of efficiencies to boost model training to deployment lead times - Understand business/product strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals. - Leverage Cloudflare products and services for AI & ML initiatives and applications - Use software engineering best practices to publish model scores/insights/learnings at scale within the company. Desirable Skills, Knowledge, and Experience - M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields. - 5+ years of ML Engineering experience with proven industry experience in a large scale environment (PBs scale & globally distributed teams) - Strong experience in scientific computing using Python with Scikit-Learn & PyTorch or Tensorflow. - Strong experience working with Docker & Kubernetes to build and deploy applications and systems. - Experience working with ML Platform tools (AirFlow, Argo Workflows, ArgoCD) preferred. - Experience working with Data Scientists to deploy Machine Learning applications systems for training, inference and observability. - Experience with Full-stack Web technologies and languages (FastAPI, Streamlit, JavaScript/TypeScrip

M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields. 5+ years of ML Engineering experience with proven industry experience in a large scale environment (PBs scale & globally distributed teams). Strong experience in scientific computing using Python with Scikit-Learn & PyTorch or Tensorflow. Strong experience working with Docker & Kubernetes to build and deploy applications and systems. Experience working with ML Platform tools (AirFlow, Argo Workflows, ArgoCD) preferred. Experience working with Data Scientists to deploy Machine Learning applications systems for training, inference and observability. Experience with Full-stack Web technologies and languages (FastAPI, Streamlit, JavaScript/TypeScript).

Deploy, manage & support ML Applications & Services on Kubernetes. Understand MLOps landscape i.e tooling, tech stack, source systems etc. and work on introducing new tools and solutions for ML & AI initiatives. Partner and align with Data Scientists, Data Engineers and internal teams to deliver ML solutions in a globally distributed environment. Lead development of efficiencies to boost model training to deployment lead times. Understand business/product strategy and high-level roadmap and align analysis efforts to enable them with data insights and help achieve their strategic goals. Leverage Cloudflare products and services for AI & ML initiatives and applications. Use software engineering best practices to publish model scores/insights/learnings at scale within the company.