Machine Learning Engineer

Available Locations - Austin, TX/Texas Highly preferred. Open to Remote US About the department
The BI team builds and operates the cloud data analytics platform for Cloudflare. We are responsible for building a centralized cloud data analytics platform using open source technologies that will be used by our internal Business Partners and Machine Learning teams. Our goal is to democratize data, support Cloudflare's critical business needs, provide reporting and analytics self-service tools to fuel existing and new business critical initiatives.

• 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.

Examples of desirable skills, knowledge and experience

• M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields.
• 3+ 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, Cloudflare Workers, etc.) preferred.
• Experience with Terraform, Google Cloud Platform (or any other public cloud equivalent), On-Premise GPUs, etc.
• Experience working with CI/CD systems, version control (Git, Bitbucket, etc.) and DevOps tools.
• Experience with Databases such as BigQuery, Postgres, SQLite and ETL/ELT practices
• Strong cross-functional collaboration experience with data engineering and data analysts teams within the function.
• Proficiency in leveraging large language models, fine-tuning and the frameworks (Langchain, Llamaindex, CrewAI, etc.) necessary for implementing GenAI applications, such as chatbots and related use cases.
• Strong communication and presentation skills catered to different audiences within the company.
• Capable of working closely with business, engineering, and product teams to ensure data initiatives are aligned with business needs.