Cloudflare - Austin, TX

posted 3 months ago

Full-time - Mid Level
Remote - Austin, TX
Professional, Scientific, and Technical Services

About the position

At Cloudflare, we are on a mission to help build a better Internet. The BI team is responsible for building and operating the cloud data analytics platform for Cloudflare. This role involves creating a centralized cloud data analytics platform using open source technologies that will be utilized by our internal Business Partners and Machine Learning teams. The goal is to democratize data, support Cloudflare's critical business needs, and provide reporting and analytics self-service tools to fuel existing and new business-critical initiatives. As part of this position, you will deploy, manage, and support Machine Learning applications and services on Kubernetes. You will need to understand the MLOps landscape, including tooling, tech stack, and source systems, and work on introducing new tools and solutions for ML and AI initiatives. Collaboration is key, as you will partner and align with Data Scientists, Data Engineers, and internal teams to deliver ML solutions in a globally distributed environment. You will also lead the development of efficiencies to boost model training to deployment lead times, ensuring that your analysis efforts align with the business/product strategy and high-level roadmap to enable them with data insights. In this role, you will leverage Cloudflare products and services for AI and ML initiatives and applications, using software engineering best practices to publish model scores, insights, and learnings at scale within the company. This position requires a strong background in machine learning engineering, scientific computing, and experience with various technologies and tools relevant to the role.

Responsibilities

  • Deploy, manage, and support ML Applications & Services on Kubernetes.
  • Understand the MLOps landscape 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 align analysis efforts to enable them with data insights.
  • 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.

Requirements

  • 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.

Nice-to-haves

  • Experience with cloud-native technologies and architectures.
  • Familiarity with data visualization tools and techniques.
  • Knowledge of data governance and compliance standards.

Benefits

  • Health insurance coverage
  • 401k benefit for retirement savings plan
  • Paid holidays
  • Flexible scheduling options
  • Professional development opportunities
  • Employee discount programs
  • Wellness programs
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