Machine Learning Engineer

Austin, TX

Applications have closed
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Posted 8 months ago

About Us

At Cloudflare, we have our eyes set on an ambitious goal: to help build a better Internet. Today the company runs one of the world’s largest networks that powers trillions of requests per month. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare have all 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 recognized by the World Economic Forum as a Technology Pioneer and named to Entrepreneur Magazine’s Top Company Cultures list.

We realize people do not fit into neat boxes. We are looking for curious and empathetic individuals who are committed to developing themselves and learning new skills, and we are ready to help you do that. We cannot complete our mission without building a diverse and inclusive team. We hire the best people based on an evaluation of their potential and support them throughout their time at Cloudflare. Come join us!  

About the department

Cloudflare is looking to grow our Business Intelligence team responsible for enabling various product and business teams such as Marketing, Sales, Finance,Customer Support, Infrastructure teams with data and analytics. Our team currently has Data Engineers, Data Analysts, and Data Scientists and we are looking to add a Machine Learning Engineer to help scale our ML platform and models.

What you'll do

  • Partner and align with data scientists, business leaders, stakeholders, product managers and internal teams to enable machine learning solutions to key business problems..
  • Understand data landscape i.e tooling, tech stack, source systems etc. and work closely with the data engineering team to improve the data collection and quality.
  • Work with data scientists to ensure best engineering practices in the deployment, maintenance, and delivery of machine learning models and insights. 
  • Use software engineering best practices to publish model scores/insights/learnings at scale within the company. 
  • Strong communication skills to communicate between engineering, data science, and product management teams.  Use storytelling skills to communicate in a crisp and concise manner.
  • Build machine learning pipelines, feedback loops, experimentation environments, and rich data sets.
  • Understand business/product strategy and high-level roadmap and align model development  efforts to help achieve strategic goals.
  • Active role in hiring, growing, and mentoring the data scientist team in Austin.

Examples of desirable skills, knowledge and experience

  • M.S or Ph.D in Computer Science, Statistics, Mathematics, or other quantitative fields.
  • Strong experience in scientific computing using Python, R, or Scala.
  • Experience with Spark, SQL, Tableau, Google Analytics, Hive and BigQuery (or any other Big data/Cloud equivalent) etc.
  • Experience working with and processing structured, unstructured, and semi-structured data.  
  • Work closely with the data engineering team to ensure robust data pipelines and model deployment.
  • 5+ years of engineering experience with proven industry experience in a large scale machine learning deployment environment.
  • 2+ years experience with a fast-growing SaaS business based company is preferred.
  • Strong communication and presentation skills catered to different audiences within the company.
  • Capable of working closely with business, engineering, and product teams to ensure machine learning  initiatives are aligned with business needs.
  • Experience in fast prototyping and establishing team engineering best practices is preferred.
  • Experience with container based deployments such as Docker & Kubernetes.
  • Experience in building RESTful and microservices applications.
Job tags: Big Data Business Intelligence Engineering Finance Kubernetes Machine Learning Marketing Python R Scala Spark SQL Tableau