Resumo da vaga

Senior Machine Learning Engineer

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

About the role

  • 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.

About the role

  • 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, Cloudflare Workers, etc.) preferred with the ability to quickly learn and contribute across a multi-language stack.
  • Experience with Terraform, Google Cloud Platform (or any other public cloud equivalent) etc.
  • Experience working with CI/CD systems, version control (Git, Bitbucket, etc.), testing (Pytest, 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 large language models and the frameworks like Langchain, LangGraph, 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.
  • Demonstrated ability to design scalable, reliable, and observable systems, with experience influencing architecture and improving platform foundations.
  • Strong problem-solving and communication skills, with a track record of working effectively with cross-functional partners and driving projects through ambiguous problem spaces.
  • Experience mentoring engineers, leading by example in code and design, and contributing to a culture of technical excellence.
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